If you give AI a topic and ask it to write a LinkedIn post that leaves out the work that makes the post worth reading: understanding your buyers, finding an interesting angle, pulling together evidence, and knowing what you can credibly say.
These 12 prompts turn that work into a repeatable system, from researching your market to building a content calendar and identifying which posts contribute to real business conversations.
Here's what you'll build:
- A voice guide based on how you actually communicate.
- A research process that finds useful ideas before you need them.
- A draft and review workflow with specific quality standards.
- A reporting loop that helps you decide what to write next.
Codex fits this work because it reads and writes the files in a project folder, so your context, research and drafts live as documents it can reopen in every thread instead of disappearing into chat history.
Save this for your next content planning session.
## Before You Run a Single Prompt: Load Your Business Context
Codex needs more than your job title and a request to "sound human." Give it enough context to understand who you sell to, what you believe, and which claims you can support.
Paste this first:
> Use the following as the working context for my LinkedIn content. Save it in a reference document I can reuse, and tell me where it is stored.
> Business: [Company name, website, product or service, and typical sales cycle].
> Audience: [Buyer roles, company sizes, industries, and locations]. Their main problems are [problems], their common objections are [objections], and the events that make them look for help are [triggers].
> Positioning: We help [audience] achieve [outcome] through [approach]. Our strongest differences are [differences]. We are not a good fit for [disqualifiers].
> Point of view: I believe [three opinions about my industry]. I disagree with [common advice] because [reason].
> Evidence: Use these approved case studies, results, examples, and personal experiences: [sources]. Do not invent customers, revenue figures, stories, or quotations.
> Voice: Here are [10-20 posts] and [transcripts or writing samples] that sound like me. Avoid [phrases, tones, and formatting habits].
> Goals: My primary LinkedIn objective is [qualified conversations / deal support / recruiting / awareness]. My offer is [offer], and the next step I want interested readers to take is [action].
> Working rules: Use connected sources only where access is available and authorized. If a source is inaccessible, ask for an export or pasted material. Keep LinkedIn publishing, comments, connection requests, and messages with me. Draft into [review destination], distinguish evidence from inference, and flag anything that needs my input.
Keep that context current as your offer, audience, and opinions change.
### Where Codex keeps this context
Give LinkedIn its own folder, for example `linkedin/`, and open it as a project in the desktop app or start `codex` inside it in the terminal. Then ask Codex to save the answer to the prompt above as `AGENTS.md` at the root of that folder. Codex loads `AGENTS.md` automatically when a session starts, so every later prompt in this guide runs on top of your business context without pasting it again. Run `/init` first if you want Codex to scaffold the file for you.
Keep `AGENTS.md` short and let it reference longer files: `context/business.md`, `context/evidence.md`, `voice-guide.md`. A working version can be this small:
```markdown
# LinkedIn workspace
Read context/business.md and voice-guide.md before any draft.
Evidence lives in context/evidence.md. Never invent customers, numbers or quotes.
Drafts go to drafts/{week}/, reviews to review/, reports to reports/.
I publish, comment, connect and message on LinkedIn myself.
Mark every claim as evidence or inference.
```
By default Codex reads at most 32 KiB of instruction files in total, so case studies and sample posts belong in separate documents that `AGENTS.md` names. Rules you want in every project, such as "never invent a quotation", can go in `~/.codex/AGENTS.md`, your personal global file. Codex merges the files from the global one down to the folder you are in, and the closer file wins, so a `drafts/AGENTS.md` can add drafting-only rules without touching the rest.
The files this guide builds up, and where Codex looks for them:
```
~/.codex/AGENTS.md personal rules for every project
~/.codex/config.toml MCP servers, web search, memory
~/.codex/review.config.toml read-only profile for prompt 8
~/.agents/skills/linkedin-draft/ reusable drafting skill
linkedin/AGENTS.md this project's context
linkedin/.codex/config.toml project-only settings
```
Codex also has memory, which can carry preferences and corrections from earlier threads (`/memories` in the CLI lets you view or reset it). It is still rolling out and may be off for your account, so treat it as a bonus: anything Codex must follow every time stays written in `AGENTS.md`.
## PART 1: RESEARCH + CONTENT PRODUCTION
Prompts 1-8
## 1. Build Your Voice Guide
A useful voice guide should explain the choices behind your writing, including how you introduce an argument, use examples, and move between ideas.
"Conversational and authoritative" won't get you very far.
> Analyze my supplied posts and transcripts to build a practical LinkedIn voice guide.
> Identify:
> How I open posts, explain ideas, and close an argument.
> My usual vocabulary, sentence lengths, paragraph lengths, and use of lists.
> How I express disagreement, uncertainty, humor, and confidence.
> Phrases I use naturally, with verbatim examples and source references.
> Writing habits that appear in weaker examples but should not become rules.
> Create a list of phrases and patterns to avoid, including unnecessary repetition, manufactured drama, unsupported certainty, and excessive one-line paragraphs.
> Finish with three before-and-after examples showing how you would edit generic copy into my voice without changing its meaning. Keep the guide specific enough that another writer could apply it.
**In Codex:** drop your best posts and a few transcripts into a `samples/` folder and mention them with `@` instead of pasting them, so Codex reads the full files rather than a truncated paste. In the desktop app you can open PDFs and docs in the sidebar preview to check what it is quoting. Ask it to write the result to `voice-guide.md`, then add one line to `AGENTS.md`: "Read voice-guide.md before drafting anything." When you catch yourself correcting the same phrase twice, ask Codex to add the rule to that file rather than hoping memory keeps it.
**Why this matters:** A good voice guide makes feedback reusable. Instead of correcting the same phrasing every week, you can improve the instructions that shape every draft.
## 2. Find the Buyer Questions Worth Answering
Your sales calls and customer conversations can reveal questions that never show up in a keyword tool. The useful ones usually involve a decision someone is struggling to make. Codex is good at this part because it can count across a folder of files instead of skimming one pasted chat.
> Review the supplied sales calls, support conversations, customer interviews, and closed-lost notes from [period].
> Group recurring questions into:
> Problems buyers are trying to understand.
> Concerns that delay a decision.
> Alternatives they are comparing.
> Expectations that lead to disappointment.
> Questions they ask right before they decide.
> For each theme, include an anonymized quotation, source reference, number of distinct conversations where it appears, buyer role, and stage in their decision.
> Suggest two LinkedIn angles per theme: one that helps the reader diagnose the problem and one that helps them evaluate a solution. Rank the top 10 by recurrence, commercial relevance, and the strength of our available evidence.
> Separate explicit buyer statements from your interpretation.
**In Codex:** export call notes into a `calls/` folder, one file per conversation, so the "number of distinct conversations" count is something Codex can actually verify. If the notes live in Gmail, Google Drive, Slack or Notion, a Codex plugin for that app can pull them in, in the desktop app, plugins sit behind a single Plugins entry in the composer's plus menu. Remember that Codex works on your files locally but the model runs in the cloud, so strip names you are not allowed to share before the run. Save the ranked list as `backlog/buyer-questions.md`.
**Why this matters:** This gives you a content backlog tied to conversations your business is already having, with language you can recognize and evidence you can check.
## 3. Find Topics Moving From X Into Your Market
A discussion gaining attention on X can become a useful LinkedIn post, provided you explain why it matters to your buyers and contribute something beyond a rewrite.
> Using live web search, any connected sources, and accessible public pages, review the last [seven days] of discussion around [topics] and these accounts: [accounts].
> Find up to 10 developments or arguments relevant to [buyer].
> For each, return:
> The original source, author, publication date, and link.
> A neutral summary of what happened or what is being argued.
> The strongest competing interpretations.
> The practical implication for our audience.
> A possible angle supported by our experience or evidence.
> Label engagement figures as a snapshot, avoid treating popularity as proof, and check factual claims against original sources where possible.
> Recommend three ideas worth developing, explaining what I would need to contribute before each becomes a credible LinkedIn post.
**In Codex:** Codex has no built-in X feed, so this prompt runs on web search. Search is on by default in a cached mode that reads a pre-indexed snapshot, which is too slow for a seven-day window. Start the session with `codex --search`, or make it the default for this folder in the project's `.codex/config.toml`:
```toml
web_search = "live"
```
If you already have links or an export of the posts you care about, put them in `research/x-links.md` and tell Codex to start from that file. In the desktop app, open the sources it returns in the built-in browser before you trust a summary.
**Why this matters:** Research gives you a starting point, your judgment gives readers a reason to follow you. A useful adaptation connects the discussion to a decision they actually face.
## 4. Analyze Posts That Outperform Their Authors' Usual Results
Comparing every post with a celebrity account's biggest hit will distort your research. Compare a post with that author's typical results first, then examine what might explain the difference. Codex can run the arithmetic as code, which is safer than asking a model to estimate medians in prose.
> Analyze this supplied LinkedIn swipe file and the available performance data: [file].
> Where enough comparable data exists, compare each post's engagement with the author's median for a similar format and period. Show the calculation and flag small samples, missing metrics, and unusually recent posts.
> For the strongest outliers, identify:
> The topic and intended reader.
> The opening, argument, supporting evidence, and closing.
> The format and approximate length.
> Whether the discussion suggests genuine buyer relevance.
> Possible confounding factors, including a launch, news event, or unusually large distribution.
> Produce five reusable structural patterns, then propose an original idea for each using my own expertise. Do not copy distinctive wording or present an observed pattern as an algorithm rule.
**In Codex:** keep the swipe file as a CSV in the project and ask Codex to compute the medians with a short script it runs itself, then show you the script next to the table. That turns "show the calculation" into something you can rerun next month. To sanity-check one post against its author's usual numbers by hand, use our [LinkedIn engagement rate calculator](/tools/linkedin/engagement-rate-calculator).
**Why this matters:** You get a more useful set of hypotheses to test, while avoiding the assumption that copying a successful post's layout will reproduce its results.
## 5. Turn Recorded Expertise Into Original Posts
A transcript can contain a strong post buried inside a story, an offhand explanation, or a disagreement that deserves more attention than it received in the original conversation. Long recordings are where a file-based agent beats a chat window: the full transcript stays on disk and gets cited line by line.
> Review this interview, podcast, webinar, or meeting transcript: [source].
> Find eight moments that could support an original LinkedIn post. Prioritize decisions, mistakes, surprising observations, practical explanations, and opinions backed by experience.
> For each moment, provide:
> The exact quotation and timestamp or source location.
> The main idea and who would benefit from it.
> Any context needed to avoid misrepresenting the speaker.
> Supporting facts already available.
> One follow-up question that would make the idea stronger.
> Select the three strongest moments and draft a post from each using my voice guide. Preserve the speaker's level of certainty, remove confidential details, and leave placeholders wherever a result or example needs confirmation.
**In Codex:** run each transcript in its own thread. The desktop app handles parallel threads in one project, so three recordings can be mined at once without mixing quotes. The summary pane in the app tracks the sources and artifacts each thread produces, which makes it easy to see which recording a quote came from. Ask for the output in `transcripts/{episode}-moments.md` with timestamps, so the drafts in prompt 7 can cite the exact line they came from.
**Why this matters:** You can produce content from expertise that already exists without asking someone to manufacture a fresh opinion every time the calendar needs filling.
## 6. Build a Four-Week Content Calendar
A calendar should balance what buyers need to understand with what you have enough evidence to say. Filling every slot with a different version of your offer makes the feed repetitive. Codex can check the plan against the backlog files it already wrote, so every slot traces to research.
> Build a four-week LinkedIn calendar at [three posts per week] using the approved ideas from our research.
> Include a mix of:
> Practical explanations that help buyers solve a problem.
> Opinions supported by experience or evidence.
> Customer examples we have permission to share.
> Answers to objections and decision questions.
> Occasional offer posts with a relevant next step.
> For each post, specify the reader, single objective, central argument, source material, suggested format, and intended reader action.
> Check for repeated topics, overlapping arguments, unsupported claims, and too many promotional posts. Write full briefs for week one and shorter outlines for weeks two through four.
> Leave room for one timely replacement each week rather than assuming the calendar must remain fixed.
**In Codex:** ask for the calendar as `calendar.csv` plus one brief file per week-one post, the desktop app previews spreadsheets, so you can review the grid without leaving Codex. Codex can also generate images, which helps you sketch a visual for a slot marked "carousel" before you build the real slides in our [LinkedIn carousel maker](/tools/linkedin/carousel-maker). For the "when" column, check [the best time to post on LinkedIn](/tools/linkedin/best-time-to-post) for your audience rather than letting Codex guess.
**Why this matters:** A useful calendar reduces weekly planning work while leaving room for better ideas, new evidence, and changes in the market.
## 7. Draft Posts With Something to Say
The research should determine the argument before Codex starts polishing sentences. Otherwise, you can end up with clean writing that takes several paragraphs to make an obvious point.
> Write three LinkedIn drafts from these approved briefs: [briefs].
> Use my business context and voice guide. For each draft:
> Make one clear argument for one intended reader.
> Open with a specific observation, tension, result, or question supported by the brief.
> Explain the reasoning with a concrete example.
> Use bullets where they make parallel points easier to scan.
> Vary sentence and paragraph length, allowing occasional one-line emphasis.
> End with a useful implication or natural next step.
> Aim for [180-300 words] unless the idea warrants a different length. Avoid repeated conclusions, invented personal stories, exaggerated promises, and formulaic contrasts.
> Supply two alternative openings and explain briefly how they change the emphasis. Flag missing evidence separately from the publishable copy.
**In Codex:** this is the prompt you will run every week, so package it as a skill. Create the folder `~/.agents/skills/linkedin-draft/` with a `SKILL.md` like this, the prompt pasted below the header:
```markdown
---
name: linkedin-draft
description: Use when I ask for LinkedIn drafts from approved briefs in briefs/.
---
Write three LinkedIn drafts from these approved briefs ...
```
Codex reads the description to decide when the skill applies, so write it as a trigger, not a summary. Then `$linkedin-draft` brings it back in any thread, and `/skills` lists what you have. In the terminal you can also park it in one of the ten `/presets` slots. Have Codex write each draft to `drafts/week-1/{slug}.md`. If a draft starts drifting into filler while Codex is still writing, send a correction right away: a follow-up sent mid-response steers it immediately instead of waiting for the end. If you want more first lines to compare with its two alternatives, run the brief through our [LinkedIn hook generator](/tools/linkedin/hook-generator).
**Why this matters:** Clear constraints give you drafts that are easier to judge. Your review can focus on the quality of the argument instead of repairing unnecessary filler.
## 8. Create a Separate Editorial Review
Give the reviewer a defined job: find weaknesses in the draft and explain how to fix them. A reassuring "This is strong" is not an editorial process. In Codex the cleanest separation is a different profile with different permissions.
> Review these LinkedIn drafts against the brief, source material, business context, and voice guide.
> Score each out of 100 using:
> Buyer relevance: 25.
> Specificity and supporting evidence: 25.
> Strength and clarity of the argument: 20.
> Match with my voice: 20.
> Readability and formatting: 10.
> Show the evidence behind each score. Check every factual claim, identify generic passages, and highlight repetitions, abrupt one-line fragments, and paragraphs that would work better as lists.
> Return a publishable revision, a short explanation of meaningful changes, and any unresolved questions. Treat invented evidence, exposed confidential information, or a misrepresented source as a blocking issue regardless of score.
> Keep everything in the review document for human approval.
**In Codex:** "separate" should mean a fresh thread, not the one that wrote the drafts. In the CLI, create a profile file `~/.codex/review.config.toml`:
```toml
sandbox_mode = "read-only"
approval_policy = "on-request"
```
Start the review with `codex --profile review`, so the reviewer can read every draft but cannot quietly overwrite one. It returns scores and the suggested revision in the thread, save them to `review/week-1.md` from your normal session, where the human approval happens. Before you approve, paste the revision into our [LinkedIn post analyzer](/tools/linkedin/post-analyzer) for a second, outside read.
**Why this matters:** A review rubric makes your standards explicit. The score helps organize feedback, while the source checks and editor's judgment determine whether the post is ready.
## The first hour after you publish
Prompt 8 ends with a revision you approve and publish. From here, every other MAXXING technique is the same: in the first hour after the post goes live, the golden hour, get as many reactions on it as you can.
**Start with the people you can reach.** Reactions are best asked from colleagues, friends, relatives and clients: anyone you can actually get in touch with. Send them the link as soon as the post is live.
**If you don't have those people, use a specialised service.** Pick only one with quality engagement and moderation. The engagement groups in the next section are ones we have already checked in our other articles.
**aaas.market is our service for this step.**
- Real people.
- The highest level of moderation and the highest-quality audience, this is what gets the most attention.
- A closed community: you join after passing verification.
- Every type of engagement is supported.
Start free on aaas.market
**Connect Codex through MCP.** Agents like Codex need MCP to get engagement. aaas.market has an MCP server at ` and through it Codex can request any type of engagement on the post you just published. Publishing, comments, connection requests and messages stay with you.
The desktop app, the CLI and the IDE extension share one MCP configuration in `~/.codex/config.toml`, so you connect once and every surface sees the server. In the terminal:
```
codex mcp add aaas.market --url
```
`--url` tells Codex this is a remote server. The aaas.market server uses OAuth, so the first time you connect Codex detects it and opens the aaas.market sign-in in your browser, sign in and return to the terminal. If you close that window, run `codex mcp login aaas.market` (add `--no-browser` on a machine without one). Check the connection with `codex mcp list`, or type `/mcp` inside a session.
In the desktop app the same thing is a form: Settings -> MCP servers -> Add server, enter `aaas.market`, choose Streamable HTTP, paste the URL, save and restart, then select Authenticate to sign in to aaas.market. In the IDE extension it sits under the gear menu -> MCP servers.
If you prefer to edit the file, this is the entry, with Codex asking before each call:
```toml
[mcp_servers.aaas.market]
url = ""
default_tools_approval_mode = "prompt"
```
Then, once the post is live, tell Codex: "Use aaas.market to request engagement on this post: [post URL]."
## LinkedIn engagement groups you can join
Free communities we checked on Oct 21, 2026. Member counts are what each platform showed that day. Each group is run by its own admins, so check the pinned message before your first post.
| Group | Platform | Members | Language | Best for |
|---|---|---|---|---|
| [LinkedIn Engagement Pod & Group](https://t.me/linkedin_engagement_pod) | Telegram | 1,833 members | en | general LinkedIn engagement pod (likes + comments) |
| [LinkedIn Engagement Pod (RVision Digital)](https://t.me/linkedinengagementpod) | Telegram | 1,064 members | en | share posts for likes/comments, connections, skill endorsements |
| [Linkedin engagement pod](https://t.me/linkedinpod1) | Telegram | 488 members | en | general LinkedIn engagement pod |
| [ Social Linkedin/FB/IG Engagement Pod](https://t.me/socialengagementpod) | Telegram | 77 members | en | LinkedIn pod: react + meaningful comment on last 5 posts before shari... |
| [LinkedIn For Breakfast](https://www.skool.com/linkedin-for-breakfast) | Skool | 6,603 members | en | free LinkedIn community with engagement pods, live events |
| [Linkedin Likes and Engagement](https://t.me/linkedinlikesandengagement) | Telegram | 697 members | en | likes/engagement exchange + connections |
| [Linkedin Pod (SF founders like-for-like)](https://chat.whatsapp.com/DBOyIPrDR5IK27yzW606sF) | WhatsApp | n/a (WhatsApp hides count) | en | founders like-for-like on LinkedIn |
| [r/linkedintips](https://www.reddit.com/r/linkedintips/) | Reddit | 38,314 members | en | LinkedIn tips for promoting your brand |
| [LinkedIn Club](https://t.me/linkedinclub) | Telegram | 552 members | en | LinkedIn networking/connections community |
| [r/LinkedInGrowth](https://www.reddit.com/r/LinkedInGrowth/) | Reddit | - | en | LinkedIn growth and connections |
Want real engagement on your own posts without searching through groups? Start free on aaas.market.
## PART 2: PIPELINE + PERFORMANCE
Prompts 9-12
## 9. Build Content Around Stalled Deals
Some of your most useful content may answer a concern that several prospects have raised privately. The goal is to explain the issue well enough that future buyers arrive better informed. This is also the prompt where Codex's access settings matter most.
> Review the supplied CRM records and call notes for qualified deals that stalled during [period].
> Identify recurring objections and distinguish:
> Explicit objections recorded in conversations.
> Possible explanations that remain unconfirmed.
> Operational delays that content is unlikely to solve.
> For each repeated objection, record the buyer role, deal stage, available evidence, and the question a useful LinkedIn post should answer.
> Recommend five content briefs. Each should explain the concern fairly, show where our approach is appropriate, acknowledge where it is not, and identify the proof required.
> Draft the two strongest posts without naming prospects or revealing deal details. Separately, suggest which approved existing resources a salesperson could share in a relevant conversation.
**In Codex:** if your CRM has a Codex plugin or an MCP server, connect it read-only, otherwise a CSV export in `crm/` works just as well. With MCP, `config.toml` lets you allow-list the tools Codex may call and make it ask before anything that is not marked read-only (the URL and tool names below are placeholders for your CRM's own):
```toml
[mcp_servers.crm]
url = "https://your-crm.example.com/mcp"
enabled_tools = ["search_deals", "read_notes"]
default_tools_approval_mode = "writes"
```
Deal data is exactly what should not end up in memory: run this where memory is off, and if you pull records through MCP, `disable_on_external_context = true` under `[memories]` in `config.toml` keeps that thread out of it. Ask Codex to keep prospect names only in the source files and use roles in every brief it writes to `briefs/stalled-deals.md`.
**Why this matters:** This connects marketing with the questions salespeople repeatedly need to answer. It also helps you avoid writing persuasive content about problems your buyers do not consider important.
## 10. Prepare Relevant Conversation Briefs
When someone responds to a post, the best next step depends on what they said and whether a business conversation would be welcome. Engagement alone does not show real business interest. Codex's job here is triage and first drafts, the relationship stays yours.
> Review these LinkedIn conversations I have supplied: [comments, inbound messages, or manually recorded interactions].
> Group them into:
> Questions that deserve a useful public answer.
> Conversations where sharing a resource would help.
> Explicit interest in our offer.
> General discussion with no commercial next step.
> For each relevant conversation, summarize the person's stated need, available business context, and what remains unknown.
> Draft a response that addresses their actual message before introducing anything else. Where appropriate, suggest one follow-up question or a resource we already have.
> Do not infer business interest from a like, invent familiarity, or force a meeting request into a conversation that does not support one. Keep all replies as drafts for me to review and send.
**In Codex:** copy the comments and messages into `inbox/this-week.md`, Codex does not read your LinkedIn inbox for you, and for this prompt it shouldn't. Ask for one reply per conversation in `replies/this-week.md`, which you edit and send yourself. For public replies under your post, our [LinkedIn comment generator](/tools/linkedin/comment-generator) gives you extra openings to compare with Codex's draft.
**Why this matters:** Preparation can make your responses more thoughtful without turning every interaction into a sales sequence. Sometimes the right outcome is simply a useful answer.
## 11. Report on Business Results With Clear Attribution
Impressions help you understand distribution, but they cannot tell you whether the right people became interested or whether a post contributed to a deal. Codex can do the joining and filtering in code, so the same report is reproducible next month.
> Combine my supplied LinkedIn analytics, tracked website visits, inbound inquiry records, and relevant CRM data for [period].
> Report on:
> Reach and engagement by post, topic, and format.
> Qualified inbound conversations.
> Resource sign-ups and demo requests where tracking exists.
> Opportunities with documented LinkedIn touchpoints.
> Content production time and review effort.
> Separate directly tracked conversions, self-reported discovery, and possible influence. Do not attribute an entire deal to LinkedIn because one contact engaged with a post.
> Highlight posts that attracted relevant buyers, posts that reached a broad but less relevant audience, and posts with insufficient data to judge.
> Finish with three findings, three limitations, and one recommended experiment. If possible, assess posts at consistent ages so newly published content is not unfairly compared with older posts.
**In Codex:** download the LinkedIn analytics export and your site and CRM exports into `data/{month}/`. Codex can join them with a script, which makes the "consistent ages" rule a filter instead of a promise. Once the report looks right, save the prompt as `prompts/monthly-report.md` and run it non-interactively, `-o` writes Codex's final answer straight to a file:
```
codex exec -o reports/2026-11.md "$(cat prompts/monthly-report.md)"
```
`codex exec` does not stop to ask for approvals the way an interactive session does, so run it by hand once and read the output before you put it on a timer. To estimate reach for posts that are missing impression numbers, use our [LinkedIn impressions calculator](/tools/linkedin/impressions-calculator).
**Why this matters:** Better reporting gives you a reason to repeat or change an approach. It also makes uncertainty visible instead of turning incomplete tracking into a confident revenue claim.
## 12. Turn Feedback Into a Better System
Every edited draft contains information about your standards. Capture the recurring lessons so you spend less time correcting familiar problems.
> Compare the original drafts, my edits, final published versions, and available performance data from [period].
> Identify:
> Voice corrections I have made repeatedly.
> Claims that needed more evidence.
> Ideas that became clearer after a change in framing.
> Formatting changes that improved readability.
> Topics that generated useful buyer conversations.
> Propose updates to the voice guide, research briefs, and editorial checklist. For every proposed rule, show an example, explain its purpose, and note when an exception may be appropriate.
> Keep stylistic preferences separate from performance hypotheses. Do not create a permanent rule from one successful or unsuccessful post.
> Return a short change log for my approval and suggest one controlled experiment for the next month.
**In Codex:** make the `linkedin/` folder a git repository and commit each draft before you edit it:
```
git add drafts/ && git commit -m "Codex drafts, week 3"
# edit the drafts yourself, then
git add drafts/ && git commit -m "My edits, week 3"
```
Codex can then read the history and `/diff` shows exactly what you changed, so "my edits" are concrete instead of remembered. Ask it to propose the new rules as an edit to `voice-guide.md` and `AGENTS.md` that you approve line by line, and to log the experiment in `experiments.md`.
**Why this matters:** This is how the workflow becomes easier to manage over time. Your corrections become usable guidance, while performance ideas remain testable rather than hardening into superstition.
## How to Use All 12 Prompts
Build the workflow in stages so you can inspect the output before adding another recurring job.
Week 1: Establish the foundation. Load your business context, run prompt 1, and check the voice guide against writing you would actually publish. In Codex that means `AGENTS.md`, `context/` and `voice-guide.md` exist and are committed.
Week 2: Build your research backlog. Run prompts 2-4 using a manageable set of customer conversations, market sources, and supplied LinkedIn examples. Turn on live search for prompt 3 and keep the median script from prompt 4.
Week 3: Produce the first batch. Use prompts 5-7 to turn approved material into a calendar and a small number of drafts. This is the week to create the `linkedin-draft` skill.
Week 4: Strengthen the review process. Run prompt 8, publish the posts you approve, use the first hour on each one, and record the changes you make. Connect the aaas.market MCP server before the first post goes out.
Weeks 5-6: Connect content with conversations. Add prompts 9 and 10 where you have enough sales context and inbound activity to make them useful. Connect the CRM read-only only now, once you know which fields you need.
Then repeat monthly: Use prompts 11 and 12 to review results, improve the instructions, and choose the next experiment.
For any recurring job, define its inputs, destination, frequency, and owner. Test a run before relying on the schedule, and have Codex report missing access or incomplete work.
Here is where each repeat job sits once the system is running:
| Job | Prompt | Where it runs in Codex |
|---|---|---|
| Weekly topic scan | 3 | Desktop automation every Monday, reusing the research thread |
| Weekly drafts | 7 | `$linkedin-draft` in a fresh thread after you approve the briefs |
| Editorial review | 8 | `codex --profile review`, read-only |
| Monthly report | 11 | `codex exec -o` from cron or CI |
| System update | 12 | A desktop thread over the folder's git history |
Codex gives you three ways to put the repeat jobs on a timer:
- **Automations in the desktop app.** Schedule the Monday research run (prompt 3) or the monthly report (prompt 11) from the app. An automation can reuse an existing thread, so it keeps the context built up there. Local scheduled runs need the computer on and the app open.
- **Codex Cloud.** Delegated runs keep going while your laptop sleeps, but only with files and access that exist in the cloud environment.
- **The CLI.** `codex exec` runs one prompt to completion, so your own cron job or CI can start the report and save it with `-o`.
While a scheduled or cloud run works, you can follow it from Codex on iOS, which shows background commands on connected hosts and lets you stop them. Codex prepares the plan, publishing stays with you. To get a nudge when each slot in the calendar comes up, put it into our [free social media scheduler](/tools/free-tools/free-social-media-scheduler): we remind you, you publish, and it is free.
You do not need 12 separate agents on day one.
Start with the job that consumes the most time and produces an output you can reliably evaluate.
## The Real Talk
Codex can help you organize research, retrieve useful evidence, prepare drafts, and learn from your edits. The quality still depends on the experience and judgment you bring into the system.
That means having a real opinion, being willing to explain it, and noticing when a polished draft says something you would never defend in a conversation.
When a post is live and you want the first hour to count, start free on aaas.market.
Otherwise, load your context into `AGENTS.md` and run prompt 1. Improving the inputs will make every step after it more useful.