Good morning.
I spent forty minutes on a call last week with an operator running a $740K expert business who could not pick between three offers. A premium small-group program, a productized audit, and a licensing play with two existing clients. He had been arguing with himself for six weeks. His team was waiting on the answer to plan the next quarter.
I asked him what his audience was buying right now from people adjacent to him, and he didn't know. I asked what those adjacent operators were charging, and he didn't know that either.
The third question was which of the three offers his existing team could deliver without him personally in the room, and he didn't have a good answer.
That's the work an Offer Agent does on a schedule, against a context file that knows your business.
Today's issue is the build. The Offer Triangle, the platform decision, full runtime prompts, and worked examples for the four business types I see most often on this list.
— Sam
IN TODAY’S ISSUE 🤖
Why this is the right agent to build
The platform paths, ranked
The Offer Triangle and the two-out-of-three trap
Seven build steps, every prompt inside
The Triangle by business type, side by side
Hand it to your team without losing the edge
A variant for solos and rebuilders
Let’s get into it.
Why You Need The Offer Agent
The Offer Agent is the build that makes the next thing you sell sharper.
Most owner-operators decide what to sell from inside their own head. They notice a pattern in customer calls, sit with it for a few weeks, argue with themselves, and pick.
The decision is binary in their thinking even when the evidence is not, and the team finds out at the launch meeting.
That pattern produces three repeating failure modes:
Failure | What it looks like | Why it happens |
|---|---|---|
Launching the wrong offer | You ship it. Nobody buys. | You decided from inside your head, not from your audience's behavior. |
Missing the right offer | Your buyers are paying a competitor for something you could have sold them. | The competitor's offer never crossed your desk. |
Pricing the work you used to do | The offer sells but your team can't deliver it profitably. | You priced the old delivery model, not the current one. |
The Offer Agent runs against all three on a recurring schedule. You get a ranked list of offer hypotheses with a thirty-day validation path attached to each one.
The work that used to live in your head and your gut sits on paper, where it can be reviewed, challenged, and acted on by people who are not you.
Three reasons this is the right second agent to build:
It changes a strategic decision from instinct to evidence. Operators who run on instinct can still be right. They just can't tell anyone how, and they can't be challenged before the launch.
It compounds with the Briefing Agent. The Briefing Agent surfaces what your prospects and customers are saying. The Offer Agent triangulates those signals against the market and your capability. Run together, they make every conversation and every offer sharper.
It surfaces capability you forgot you had. The capability stream is often where operators are most blind, because the work their team is doing today rarely matches the work the operator thinks the team is doing.
This is also the second move in the Digital Employee frame.
The Offer Agent is the strategy associate. You manage it the way you would manage a strategic hire:
A clear job description (the system prompt)
A defined set of inputs it scans every cycle (the context file)
A review meeting on what it produced (you read the Triangle output, you challenge it, you ship the offer that survives)
A widening remit over time (more business lines, more granular pricing experiments, more frequent runs)
That mental model keeps you from treating the agent's output as decisive. The Triangle output is a strong first draft of an offer decision. You and the people you trust are the ones who ship it.
The Platform Decision (Read It Once, Decide, Move On)
Same options that I recommend. Consistency across builds keeps your context portable.
Path | Best for | What you get | What to know |
|---|---|---|---|
Claude Code in Cowork mode (or just Code) | Operators already in Claude | Folder-based context file you can version and edit; reusable skill scaffolding from the Briefing Agent | The path I run on. Lowest setup if you already have a Claude workflow. |
The OpenAI Codex app | Operators in Microsoft 365, Slack, or Notion | Persistent memory across runs, plugins for the apps your sales notes live in | The April release made this a real candidate. Triangle output sharpens cycle over cycle. |
Quick Decision Rule
Already in Claude? Use Cowork mode.
Already in Microsoft 365, Slack, or Notion? Use the Codex app.
The Offer Triangle
The mistake most operators make when they try to use AI for offer strategy is asking the model a flat question. "What offer should I launch next?"
The model produces a plausible answer, and the plausibility is the problem. The output sounds like strategy without sitting on any specific intelligence about your audience, your market, or your capability.
The Offer Triangle is the structure I run on every offer decision worth making. It pulls three streams of intelligence in parallel and meets them at a synthesis surface.
An offer only counts as a real recommendation when it hits all three sides. Two-out-of-three hits get flagged as traps, because those are the offers that feel right and fail anyway.
The Three Streams At A Glance
Stream | What it answers | Where the inputs come from | What it produces |
|---|---|---|---|
A. Audience | What are your buyers buying, asking for, or paying competitors for that you don't sell? | Sales notes, customer interview transcripts, community and list responses, your own customer conversations in the last quarter | Repeated buying patterns, named asks the current stack doesn't serve, named alternatives they're purchasing instead |
B. Market | What's offered at your audience layer, by whom, at what price, and where are the structural gaps? | A named list of 5-10 competitors and adjacent operators, their public surfaces, recent category commentary | Offer shape by competitor, price bands, unserved price points and packaging shapes |
C. Capability | What can you profitably deliver with the team and tools already in place? | Your offer stack as it exists, team composition, unit economics, honest read on bandwidth for the next 90 days | Deliverability rating, gross margin band, time-to-first-dollar for each candidate offer |
The Synthesis Surface
The agent reads all three streams in sequence, then maps every candidate offer against all three sides and flags the geometry. The Triangle output gives you:
A ranked list of offer hypotheses (typically three to seven)
For each one, an explicit read on which Triangle sides it hits
For two-out-of-three offers, the named gap and the lowest-cost path to closing it
For each real recommendation, a thirty-day validation path: who you talk to, what you test, what the kill condition is
You read the output, challenge it, and pick what to validate. The agent does the diligence work. You stay the decision-maker.
Why The Geometry Matters
Most offer failures are two-out-of-three failures. Each one has a different shape and a different fix:
The hit | The miss | What it looks like in the market | The fix |
|---|---|---|---|
Audience + Market | Capability | People wanted it. Competitors weren't offering it. Your team couldn't deliver it profitably, or it required hiring you didn't do. | Hire, partner, or scope down. Don't ship the original offer. |
Audience + Capability | Market | You could deliver it. Your buyers were buying it. The layer was saturated and your pricing died on the page. | Reposition or reprice against the saturated layer. Differentiate on something the layer ignores. |
Market + Capability | Audience | A gap existed. You could fill it. Your buyers were not the ones buying that shape. | Find the buyer this offer is for, or kill the offer. |
The Triangle names which fix is required, before you spend three months building the offer and a quarter selling it.
The Protocol
Seven steps. Every prompt below is usable as written.
Step 1: Pick The Platform And Confirm Access
Pick Claude Code in Cowork mode or the Codex app based on the decision section above. Confirm the agent has access to:
Web browsing or Perplexity
The folder or workspace where the context file and Triangle outputs will live
Your sales notes (CRM export, Notion database, or local folder)
Your customer interview transcripts if they exist (Fireflies, Granola, Fathom, or local folder)
You do not need a full data warehouse to run this agent. You need a structured way for the agent to read your sales conversations and your customer interviews. A monthly export of sales notes into a markdown file is enough.
Step 2: Build The Context File
This is the single most important step in the build. The Offer Agent is only as sharp as the picture of your business and your market it can read.
Create a markdown file the agent will reference on every run. Name it offer-context.md and put it in the folder or workspace the agent has access to. Fill it out once. Update it monthly.
# Offer Context
## About The Business
- Business name, what you sell, who you sell to.
- Annual revenue band and approximate breakdown across current offers.
- Team composition: roles, headcount, who owns delivery.
- The three positions your business takes in your market that distinguish you.
## The Current Offer Stack
- Each existing offer, in plain language.
- Price point or price range for each.
- Gross margin or rough margin band for each.
- Who delivers each offer (you, a specific team member, the team as a unit).
- The bottleneck on each offer (your time, a specific role, a tool, a process).
## Audience Profile
- Who your current best buyers are (segment, size, role, budget band).
- The two or three buying patterns you've seen repeated across them in the last 90 days.
- What they've told you they want that you do not currently offer.
- What you've heard them say they're paying adjacent operators for.
## Competitive Layer
- Five to ten competitors or adjacent operators at your audience layer, by name and URL.
- The two or three offers from each one you're aware of, with rough price points.
- Any recent launches, repositioning, or category moves you've noticed in the last 90 days.
## Capability Read
- What your team has bandwidth to build or deliver in the next 90 days without new hires.
- What you could deliver in 90 days with one new hire or one new tool, named.
- What's out of reach in 90 days no matter what.
## Honest Constraints
- The kinds of work you will not take on (no done-for-you, no enterprise procurement cycles, etc.).
- Any commitments to current customers or partners that bound the offer space.
- The minimum gross margin you'll accept on a new offer.
## What The Offer Agent Should Always Surface
- Any offer hypothesis that hits all three sides of the Triangle.
- Any two-out-of-three hypothesis with a named, low-cost path to closing the gap.
- Any audience-side signal that contradicts a position the business currently holds.
- Any market move from a named competitor that changes the geometry of an existing offer.
## What The Offer Agent Should Never Do
- No generic offer suggestions (course, community, mastermind) that aren't grounded in evidence from at least one stream.
- No invented competitor offers or invented price points. If a fact isn't sourced, mark it as inferred.
- No language like "innovative", "premium", "next-generation", or "transformative". Describe the work.
- No recommendations the team cannot deliver in the next 90 days unless that's explicitly flagged as a strategic build.
This file is the difference between a generic strategy bot and an agent that returns offer recommendations grounded in your specific business and your specific market.
The Tacit-to-Explicit Knowledge work happens here. Everything you know about your buyers, your competitive layer, and your team's real bandwidth lives in your head. The context file is the deliberate act of moving that knowledge out into a place the agent can use.
Step 3: Install The System Prompt
This is the agent's job description. Put it in a file called offer-agent-system-prompt.md in the same folder.
You are the Offer Agent for [Business Name].
Your job is to produce a Triangle output that ranks offer hypotheses and flags traps, on a recurring schedule.
Read offer-context.md before every run. Everything in that file takes precedence over your defaults.
You will run three sequential intelligence passes, then a synthesis pass. The three streams are: Audience, Market, Capability. The synthesis is the Triangle.
PASS A: AUDIENCE
Read every sales note, customer interview transcript, and audience signal in the connected sources from the last 90 days. Pull out:
- The repeated buying patterns you observe (what they're buying, from whom, at what price band).
- The named asks you see that nobody in the current offer stack serves.
- The named alternatives you see being purchased that the business does not currently offer.
- Anything an audience member said about price, value, or unmet need that should be flagged for the offer hypothesis pass.
Cite sources inline as ([Source Type, Date]) where the source is the file or transcript and the date is the date of the conversation or interview. Do not invent audience signals. If a category has no data, write "No signal in current sources."
PASS B: MARKET
Read the named competitive layer in offer-context.md. For each competitor and adjacent operator, find their current offers, price points, and any launches or repositioning in the last 90 days. Look at their public pricing pages, sales pages, newsletters where accessible, and credible category commentary.
Produce a market map: offer shape by competitor, price band by offer, structural gaps where price points or packaging shapes are unserved at this audience layer. Cite sources inline. Do not invent competitor offers or prices. If you cannot verify, mark as "inferred" with the basis for the inference.
PASS C: CAPABILITY
Read the current offer stack, team composition, and capability section of offer-context.md. For each candidate offer that has surfaced from Passes A and B, rate it on:
- Deliverability with the current team in the next 90 days (yes, with one named addition, or no in 90 days)
- Gross margin band given the current delivery model
- Time to first dollar (under 30 days, 30-60 days, 60-90 days, over 90 days)
PASS D: TRIANGLE SYNTHESIS
Combine the three priors into the Triangle output using the exact template below. Do not deviate from the template. Do not pad. If a section has nothing real to surface, write "No candidate this cycle" rather than filling space.
TEMPLATE:
# Offer Triangle: [Date]
Scope: [The business unit or scope this run is covering, if relevant]
## Audience in 90 Seconds
[Three short paragraphs. The repeated buying patterns, named asks, and named alternatives from Pass A. Cite at least three sources.]
## Market in 90 Seconds
[Three short paragraphs. Current offer shapes, price bands, structural gaps from Pass B. Cite at least three sources.]
## Capability Read
[Two short paragraphs. The team's delivery capacity, the candidate work that fits the current model, the candidate work that does not.]
## Ranked Offer Hypotheses
For each hypothesis (three to seven):
### Hypothesis [N]: [Name of the offer in plain language]
- Triangle hit: [All three sides / Audience + Market / Audience + Capability / Market + Capability]
- Audience evidence: [Specific signal with source]
- Market evidence: [Specific signal with source]
- Capability evidence: [Specific signal from context file]
- If two-out-of-three: the named gap, and the lowest-cost path to closing it
- 30-day validation path: who to talk to, what to test, what the kill condition is
## This Cycle's Recommendation
[One paragraph. Which hypothesis you would put into validation first, and why. No more than one paragraph. The point is a clear next move, not a survey of options.]
A couple of things this system prompt is doing under the hood:
It forces three real intelligence streams before the synthesis. Skipping any of the three produces a flatter output, and operators who use it without the discipline of the three streams end up back where they started, picking offers from inside their own head.
It bans invented evidence with explicit "no" language. The model will still occasionally try to invent a competitor offer or price. The "do not invent" clause and the citation requirement cut the slip rate substantially in my testing without driving it to zero. You catch the slips on review.
Step 4: The Four Pass Prompts
These are the runtime prompts you send when you want a Triangle output produced. The system prompt above governs the agent's behavior across all four passes. The prompts below trigger each pass in sequence.
Pass A prompt (Audience):
Run Pass A of the Triangle.
Read every sales note, customer interview, and audience signal in the connected sources from the last 90 days. Produce the AUDIENCE section only.
Pull out the repeated buying patterns, the named asks that the current offer stack does not serve, and the named alternatives audience members are purchasing instead. Cite each signal inline with its source file and date.
Do not produce any other sections in this pass. Do not generalize from one signal. If a pattern is supported by fewer than two independent observations, mark it as a single-source signal.
Pass B prompt (Market):
Run Pass B of the Triangle.
Read the named competitive layer in offer-context.md. For each competitor and adjacent operator, find current offers, price points, and any launches or repositioning in the last 90 days.
Produce the MARKET section. Output as: offer shape by competitor, price band by offer, structural gaps where price points or packaging shapes are unserved.
Cite sources inline. If a competitor's pricing is not public, say "not public" rather than estimating. If you have to infer, mark it as "inferred" with the basis.
Pass C prompt (Capability):
Run Pass C of the Triangle.
Take the candidate offers that have surfaced in Pass A and Pass B. For each one, rate it on:
- Deliverability with the current team in the next 90 days (yes / yes with one named addition / no in 90 days)
- Gross margin band given the current delivery model
- Time to first dollar (under 30 days / 30-60 / 60-90 / over 90)
Pull only from offer-context.md and any conversation history we have on team capacity. Do not assume capability the context file does not describe.
Pass D prompt (Synthesis):
Run Pass D. Produce the full Triangle output using the TEMPLATE in your system prompt.
Pull from the work you did in Passes A, B, and C.
For each hypothesis, name the Triangle hit explicitly. For every two-out-of-three hypothesis, name the missing side and the lowest-cost path to closing the gap. For each real recommendation, write the 30-day validation path with a named kill condition.
Close with one paragraph naming the hypothesis to put into validation first. No more than one.
Deliver as a markdown document I can review on a laptop in twenty minutes.
Step 5: Run Your First Triangle
Pick a real strategic question on your plate this quarter. The candidate offer you've been arguing with yourself about for six weeks is the right place to start. Send the four passes in sequence, and pay attention to what each one surfaces:
Pass | What to read for |
|---|---|
Pass A | Audience signals the agent surfaces that you forgot you had |
Pass B | Competitive moves you missed |
Pass C | Where your honest read on capability differs from the agent's |
Pass D | The Triangle output |
The first run will be 80% there. Expect:
Audience section sharp where your notes are good, thin where they aren't
Market section roughly right
Capability section honest in the places your context file is honest, soft in the places it isn't
Synthesis naming two or three hypotheses that should not surprise you, and probably one that should
Take the output into a real strategic review with whoever in your business helps you make these calls. Argue with it. Note where you disagreed and why.
Step 6: Tune After Three Runs
Three real Triangle outputs in, you'll have a clear sense of where the agent is over-producing and where it's under-producing. Update the context file with the corrections. Tighten the "what the offer agent should never do" section based on what it kept doing anyway.
Four common tunes after three runs:
Anchoring on your current offer stack. The agent keeps surfacing hypotheses that look like adjacent variations of what you already sell. Add to the context: "Surface at least one hypothesis per run that does not share delivery infrastructure with the current offer stack."
Recency bias on fashionable categories. The agent over-weights the offers that are trending in your category. Add: "A hypothesis is not stronger because it's in a fashionable category. Score evidence on volume of audience signal in the last 90 days, not on category momentum."
Capability over-estimation. The agent rates an offer as deliverable that your team cannot ship in 90 days. Tighten the capability section: "If a hypothesis requires a hire you have not committed to, rate it as 'yes with one named addition' and name the role and the cost."
Triangle washing. The agent labels too many hypotheses as "all three sides" by stretching the evidence. Add: "A hit on a Triangle side requires a cited source. Inferred evidence does not count as a hit."
Step 7: Set The Schedule
The Offer Agent runs on a slower cadence than the Briefing Agent. The Briefing Agent runs every day because the meetings change every day. The Offer Agent runs every two to four weeks because the underlying intelligence does not change fast enough to justify weekly runs.
Both Claude Code in Cowork mode and the Codex app support scheduled automations. Set the agent to run a full four-pass Triangle on a fixed day every other Monday morning, or on the first Monday of each month, depending on the velocity of your business.
The Triangle output lands in your inbox or designated folder, you scan it that morning, and you bring the strongest one or two hypotheses into the next strategic review on your calendar. Decisions about what to sell next stop being a thing you carry in your head between cycles.
What This Looks Like By Business Type
The Offer Agent stays the same. The inputs and the kinds of offers it surfaces change with the business. Here's the Triangle by business type, side by side:
Agency | SaaS | Ecommerce | Expert / Creator | |
|---|---|---|---|---|
Audience inputs | Sales conversations, win / loss notes, customer interviews | Product usage data, support conversations, customer success notes | Purchase data, reviews, support tickets, last quarter of customer messages | Sales calls, discovery questions, community / list responses, customer interviews |
Market reads | Adjacent agencies, productized offerings emerging at your scale | Competitors and adjacent products in your buyer's stack | Direct competitors and adjacent merchants, product mix, price laddering, recent launches | Experts and creators at your level, offer ladders, recent launches |
Capability against | Existing delivery pod, retainer load | Current product roadmap, engineering capacity | Supplier relationships, fulfillment infrastructure, inventory commitments | Your time, team's leverage, assets you already own |
Typical hypothesis shapes | Productized version of custom work; sister offer for the same team at a different point in the buying cycle; strategic offer (audit, roadmap, advisory) | Higher-tier feature bundle the audience is already buying from someone else; integration / workflow offer; services or implementation offer the product team resists | Higher-margin SKU or bundle for your most active buyer segment; category extension; subscription or replenishment shape | Productized version of bespoke work; group or cohort offer; licensing or platform offer that decouples revenue from your hours |
Watch-Out | Senior bandwidth. Agencies over-estimate delivery capacity. | Margins. Services dilute SaaS economics. | Supplier and inventory. Ecommerce operators rush past Capability. | Identity. Experts refuse offers the Triangle recommends because they don't feel like them. |
The pattern across all four: the Triangle output is short, dense, and grounded in real inputs from your business. You read it once and you have a clearer read on what to ship next than you do after a six-week argument with yourself.
A Note On The Watch-Outs
The Watch-Out row is where the Triangle earns its keep across business types. Every business shape has a stream the operator habitually under-weights, and the agent's job is to slow you down there. Read the Hypotheses row for the upside. Read the Watch-Out row for the trap, because that's the row that decides whether the upside is real.
Deploying This Across Your Team
The Offer Agent works as a solo build. It compounds when the people in your business who own offer strategy and growth are using it too.
Four pieces of ownership keep this clean:
You own the architecture. The context file, the system prompt, and the Triangle template are your IP. They live in a shared folder your strategy or growth lead can read but not modify. That permission boundary keeps Triangle outputs comparable across cycles.
The strategy or growth lead runs the cycle. They send the four passes on the schedule, they collect the output, they prep the strategic review with the Triangle on the agenda. You stop being the person sending the prompts.
The team challenges the output. The Triangle is a first draft of an offer decision, not a verdict. The right meeting cadence is a thirty-minute review where the head of sales, the head of delivery, and you all push on the hypotheses before any of them become a launch.
You own the kill conditions. Every offer that goes into validation has a named kill condition: a date, a metric, a missed signal. The agent surfaces them. You ratify them. The team enforces them.
The compound effect is the same one I named in the Briefing Agent build, applied one layer up. Offer decisions stop being a function of the operator's gut on a given Thursday and become a function of three streams of evidence meeting at a synthesis surface every cycle. The next thing you sell is the offer that survived the Triangle, the strategic review, and a thirty-day validation, and both your hit rate and your launch velocity go up.
Bonus: The Early-Stage Variant
Some operators on this list are solo, pre-revenue, or rebuilding after a previous offer ran its course. The full Triangle is still the right architecture. The inputs change. Here's the swap:
Stream | Standard build (established business) | Early-stage build (solo, pre-revenue, rebuilding) |
|---|---|---|
A. Audience → Demand Discovery | Sales notes, customer interview transcripts, community responses, customer conversations in the last quarter | The last 20 conversations you've had about your work, a single targeted question posted in 3 communities you trust, public commentary from operators one or two levels ahead on what they've been buying |
B. Market → Market Scan | 5-10 named competitors at your audience layer, their pricing pages and public surfaces, recent category commentary | Operators 6-12 months ahead of you on the same path, their public surfaces, pricing pages where they exist, recent launches |
C. Capability → Capability Inventory | Current offer stack, team composition, unit economics, bandwidth for the next 90 days | The work you've already done (formally or informally) that you can point at as evidence of delivery, listed the way an experienced operator would list a team |
Two rules that hold the early-stage variant together:
Weight a small corpus deliberately. The context file should name the surfaces explicitly and tell the agent to treat them as audience evidence even though the corpus is small. The discipline of the three streams matters more than the volume of inputs.
Map the market you can ship into now. Resist the temptation to map your eventual market. The Triangle should surface the offer you can ship in the next ninety days. The three-year version of your business is a separate conversation.
The Triangle output for an early-stage operator usually ranks three to five offer hypotheses with a clear winner: a productized version of work you've already done, at a price point you can defend by reference to operators one level ahead, with a 30-day validation that involves five real conversations.
This variant exists because the audience for this newsletter spans operators with established businesses and operators rebuilding what they sell. The agent works for both. The discipline of the three streams is what makes the build worth running.
Want The Full Agent Build Pack?
You can build most of the Offer Agent from the prompts above.
But if you'd rather skip the setup work, and get bonus content, Cortex subscribers get the full Offer Agent Build Pack as a download:
The installable Claude Skill that sets up the agent in Cowork mode in one command
The Codex configuration pack with system prompt, plugin list, and scheduled-automation specs for the every-other-week Triangle run
Four pre-filled context files (agency, SaaS, ecommerce, and expert / creator) with real-feeling offer stacks, competitor lists, and capability reads you can adapt instead of starting blank
The Tune Pack: the most common drift patterns I've seen for this agent (anchoring traps, recency bias on fashionable categories, capability over-estimation, Triangle washing), with the exact context-file edits and prompt patches that fix each one
Three examples of Triangle outputs with annotations on why each hypothesis was ranked as it was
This is only available to paying Cortex subscribers.
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Run the Offer Agent for a quarter and you stop arguing with yourself about what to sell next.
The argument gets externalized into three streams of intelligence meeting at the Triangle, and the output sits on paper where your strategy lead and your head of sales can push on it before anyone commits to a launch.
The operators on the other side of the table from your buyers are almost certainly still picking offers from the top of their heads.
They will not be doing that in two years, and the window where running an Offer Agent is itself an edge is open right now.
Talk soon,
Sam Woods
The Editor
.
