How to Build a Software Factory With Opus 4.8, GPT 5.5 and Kimi 2.6

This is a complete A-Z guide on how to build the most powerful workflow between Claude Opus4.8, Chat GPT 5.5, and Kimi K2.6.

Most people use AI coding tools wrong.

They open Claude.

Ask it to build the whole app.

Wait.

Hit the rate limit.

Wait again.

Paste the error.

Hit the limit again.

And after 2 hours, they are still fixing the same broken dashboard.

That is not a software factory.

That is expensive vibe coding.

The real workflow is different.

You do not use one model for everything.

You use each model for the job it is best at.

Claude Opus 4.8 is incredible for thinking.

But it is expensive.

Opus 4.8 costs $5 per 1M input tokens and $25 per 1M output tokens.

Kimi K2.6 is much cheaper.

Kimi is around $0.95 per 1M input tokens and $4 per 1M output tokens.

Cached input can go even lower.

GPT 5.5 is very good at fixing bugs, generating assets using gpt-image-2

So why burn Claude on:

→ boilerplate

→ CRUD screens

→ Tailwind fixes

→ auth setup

→ API routes

→ refactors

→ repeated error loops

Use Claude where judgment matters.

Use Kimi where execution matters.

And the best part:

Kimi is not just one more chat app.

Kimi Code works inside your terminal and IDE.

It runs on \kimi-for-coding\, powered by Kimi K2.6.

The same Kimi membership can be used for research and coding workflows.

You can use Kimi for:

→ deep research

→ agent swarm

→ web search

→ codebase analysis

→ file editing

→ command execution

→ subagents

→ coding inside terminal

→ coding inside VS Code

This is the complete workflow.

Save this. It will change how you build.

PART 1: THE SOFTWARE FACTORY MINDSET

(Stop treating AI like one chatbot)

1. One Model Is Not a Team

Most builders still ask one model to do everything.

Research the market.

Write the spec.

Design the UI.

Generate icons.

Build the backend.

Fix bugs.

Review the code.

Write the landing page.

That sounds convenient.

But it breaks fast.

Every task has a different shape.

Research needs breadth.

Product specs need judgment.

Design needs visual direction.

Building needs cheap iteration.

Review needs careful reasoning.

One model can do all of this.

But one model should not do all of this.

The software factory is a routing system.

Each model gets the job it is best at.

Before building anything, create the factory rules.

2. Why Claude Should Not Build Everything

Claude Opus 4.8 is one of the best models for deep thinking.

Use it for:

→ product judgment

→ architecture decisions

→ PRD writing

→ edge cases

→ code review

→ strategy

But do not waste it on the 2-hour build loop.

Building is messy.

You will ask for changes.

You will regenerate files.

You will run tests.

You will paste errors.

You will fix styling.

You will change database fields.

You will rewrite the same component 4 times.

This is where Claude rate limits hurt.

Not because Claude is bad.

Because you are using an expensive thinking model for cheap repetitive execution.

Claude should be the architect.

Not the intern writing the same form again and again.

3. The Pricing Difference Changes the Workflow

Token cost matters when you are building.

Not in theory.

In the actual loop.

Claude Opus 4.8 API pricing:

→ $5 per 1M input tokens

→ $25 per 1M output tokens

Claude Opus 4.8 fast mode:

→ $10 per 1M input tokens

→ $50 per 1M output tokens

Kimi K2.6 API pricing:

→ around $0.95 per 1M input tokens

→ around $4 per 1M output tokens

→ cached input can be much cheaper

Kimi Code:

→ included as a Kimi membership coding benefit

→ works in terminal

→ works in VS Code

→ can be connected to third-party coding agents

→ uses shared membership quota

→ powered by Kimi K2.6 through \kimi-for-coding\

That means one model is better for expensive decisions.

The other is better for high-volume execution.

Claude is where you spend carefully.

Kimi is where you iterate aggressively.

This is the unlock.

The question is not:

"Which model is better?"

The question is:

"Which model should do which job?"

PART 2: RESEARCH WITH KIMI AGENT SWARM

(Find products worth building before writing code)

4. Use Kimi as a Research Organization

Start with Kimi.

Not for coding.

For research.

Open Kimi.

Use Kimi Agent Swarm / Deep Research.

You can start from the same Kimi ecosystem you will later use for coding.

Then switch to Kimi Code when it is time to build.

Kimi Code can run in your terminal or VS Code.

It can read files, edit files, execute commands, search the web, and spawn subagents.

That means the same Kimi subscription can support both sides:

→ research

→ coding

This is why it fits the factory workflow.

You are not buying one tool for research and another tool for building.

You are using Kimi as the cheap high-volume layer.

Give it a massive prompt and make it act like a startup research organization.

Do not ask:

"Give me 10 startup ideas."

That gives you obvious garbage.

Ask it to spawn research agents.

Each agent should search a different market signal.

→ Reddit pain points

→ Quora questions

→ G2 reviews

→ Capterra complaints

→ App Store reviews

→ Play Store reviews

→ YouTube comments

→ LinkedIn posts

→ job postings

→ competitor pricing pages

→ niche forums

→ industry reports

The goal is evidence.

Not imagination.

You want pain people already talk about.

You want products people already pay for.

You want broken workflows nobody has fixed properly.

Use this prompt:

1KIMI AGENT SWARM RESEARCH PROMPT
2You are an autonomous startup opportunity discovery organization.
3You are not a single researcher.
4You must spawn many independent research agents and subagents in parallel.
5Your objective:
6Find high-conviction startup, SaaS, AI agent, app, B2B, SMB, enterprise, marketplace, and D2C product opportunities that an indie hacker or solo app developer can realistically build and sell.
7Do not brainstorm.
8Conduct evidence-based opportunity discovery.
9Target audience:
10- indie hackers
11- app developers
12- solo founders
13- AI builders
14- micro-SaaS founders
15- developers who can build fast but need better ideas
16Strongly prioritize:
17- boring businesses
18- operational software
19- industries without tech teams
20- spreadsheet-heavy workflows
21- WhatsApp workflows
22- repetitive manual tasks
23- compliance pain
24- labor replacement
25- high-margin industries
26- hidden niches
27- fragmented markets
28- workflows where AI can remove human admin work
29Avoid:
30- generic ChatGPT wrappers
31- social apps
32- consumer apps with no willingness to pay
33- viral-only ideas
34- "Uber for X"
35- ad-based businesses
36- hyper-competitive AI tools
37- ideas that require huge teams or venture funding
38Spawn the following agents:
391. Pain Point Mining Agents
40Search:
41- Reddit
42- Quora
43- niche forums
44- Discord communities
45- Slack communities
46- Facebook groups
47- LinkedIn discussions
48- YouTube comments
49Look for phrases like:
50- "I hate this"
51- "there has to be a better way"
52- "why is this still manual"
53- "looking for software that"
54- "what do people use for"
55- "Excel hell"
56- "this takes forever"
57- "we still do this in WhatsApp"
58- "our current tool sucks"
59- "too expensive"
60- "too complicated"
61Output:
62List recurring pains with source links, exact wording, frequency, and buyer type.
632. Vertical SaaS Agents
64Spawn one agent for each vertical:
65- clinics
66- dentists
67- hospitals
68- diagnostics
69- real estate brokers
70- property managers
71- interior designers
72- construction companies
73- warehouses
74- logistics firms
75- distributors
76- restaurants
77- hotels
78- gyms
79- schools
80- coaching businesses
81- CA firms
82- tax consultants
83- legal offices
84- recruiters
85- staffing agencies
86- insurance brokers
87- wealth managers
88- small manufacturers
89- franchises
90- home service businesses
91- ecommerce sellers
92- D2C brands
93For each vertical, identify:
941. Major workflows
952. Manual tasks
963. Expensive bottlenecks
974. Compliance burdens
985. Spreadsheet dependencies
996. WhatsApp/email dependencies
1007. Current tools
1018. Why current tools fail
1029. Who pays
10310. Fastest MVP opportunity
1043. Competitor Intelligence Agents
105Research:
106- pricing pages
107- G2 reviews
108- Capterra reviews
109- Trustpilot reviews
110- app reviews
111- Reddit criticism
112- changelogs
113- support complaints
114- feature requests
115Find:
116- overpriced products
117- poor UX
118- missing automation
119- weak onboarding
120- slow support
121- feature gaps
122- products users tolerate but do not love
1234. AI Agent Opportunity Agents
124Find jobs that can become:
125- AI copilots
126- AI analysts
127- AI back-office workers
128- AI operations assistants
129- AI sales assistants
130- AI support agents
131- AI compliance reviewers
132- AI reporting agents
133Prioritize workflows with:
134- high repetition
135- text-heavy work
136- expensive labor
137- documentation
138- manual review
139- reporting
140- data entry
141- customer follow-up
142- internal coordination
1435. Validation Agents
144Destroy weak ideas.
145For every opportunity, ask:
146- Is the pain frequent?
147- Is the pain expensive?
148- Is someone already paying for a solution?
149- Is the buyer obvious?
150- Can we reach the buyer?
151- Can an MVP be built in 2 weeks?
152- Can AI create a 10x improvement?
153- Why has this not been solved already?
154- Is this just a feature, not a business?
155- Would someone pay $50, $200, $500, or $2,000/month for this?
156Reject ideas aggressively.
1576. Synthesis Agent
158Merge all findings.
159Remove duplicates.
160Cluster similar opportunities.
161Rank the best ideas.
162Scoring weights:
163- Pain severity: 25%
164- Willingness to pay: 20%
165- Market gap: 15%
166- Ease of execution: 10%
167- Distribution: 10%
168- AI leverage: 10%
169- Market timing: 10%
170For each opportunity, provide:
1711. Opportunity title
1722. Industry
1733. Category
1744. Exact pain point
1755. Evidence with source references
1766. Existing alternatives
1777. Why existing products fail
1788. ICP
1799. Buyer
18010. Buying power
18111. Revenue model
18212. MVP complexity from 1-10
18313. Time to MVP
18414. Distribution difficulty from 1-10
18515. Why now
18616. AI leverage
18717. Defensibility
18818. Risk level
18919. 2-week MVP scope
19020. First 10 customer acquisition strategy
19121. Estimated revenue potential
19222. Confidence score from 0-100
19323. Final recommendation
194Final deliverable:
195Return:
196- 100 raw opportunities
197- 25 highest-conviction opportunities
198- top 10 fastest-to-revenue opportunities
199- top 5 best opportunities for a solo developer
200- top 3 I should build first
201Do not make the answer motivational.
202Be brutally practical.
203Reject weak ideas.
204Prioritize evidence.

5. What Kimi Should Find

The best opportunities are usually boring.

Not "AI girlfriend."

Not "social app for founders."

Not "ChatGPT wrapper for productivity."

Look for:

→ spreadsheet-heavy businesses

→ WhatsApp-based operations

→ manual reporting

→ compliance work

→ expensive labor

→ repetitive admin

→ bad legacy software

→ industries without tech teams

→ workflows still done by email

→ tasks people hate doing every week

Examples:

Clinics.

Property managers.

CA firms.

Recruiters.

Warehouses.

Distributors.

Interior designers.

Schools.

Hotels.

Construction companies.

These businesses do not want AI demos.

They want time saved.

They want fewer mistakes.

They want more revenue.

They want software that removes pain.

That is what Kimi should find.

6. Make Kimi Kill Weak Ideas

Most startup ideas sound good for 5 minutes.

Then they die when you ask real questions.

So make Kimi destroy weak ideas.

For every opportunity, ask:

→ Is this painful enough?

→ Are people already paying?

→ Why has nobody solved it?

→ Can an MVP be built in 2 weeks?

→ Can I reach the first 10 customers?

→ Is the buyer obvious?

→ Is the workflow repeated often?

→ Can AI make it 10x better?

Reject aggressively.

You do not need 100 ideas.

You need 1 idea with evidence.

The output should be:

Top 25 opportunities ranked by:

→ revenue speed

→ ease of execution

→ evidence strength

→ distribution

→ AI leverage

→ founder leverage

Now you have something worth building.

PART 3: WRITE THE PRD WITH CLAUDE OPUS 4.8

(Turn research into a product people can understand)

7. Bring in Claude Only After the Research Is Done

Once Kimi finds the best opportunity, stop researching.

Now use Claude Opus 4.8.

This is where the expensive model makes sense.

Give Claude:

→ the top opportunity

→ pain point evidence

→ ICP

→ competitor gaps

→ workflow details

→ pricing ideas

→ 2-week MVP scope

→ first 10 customer strategy

Then ask it to write the PRD.

Claude should turn messy research into a clean product spec.

This is the step most indie hackers skip.

They jump straight into coding.

Then they build a product with:

→ no clear user

→ no clear workflow

→ no clear pain

→ no clear buyer

→ no clear reason to pay

The PRD fixes that.

Use this prompt:

1CLAUDE OPUS 4.8 PRD PROMPT
2You are a senior product strategist, startup CTO, and technical product manager.
3I am giving you validated startup opportunity research from Kimi Agent Swarm.
4Your job:
5Turn this messy research into a complete PRD for a 2-week MVP that a solo indie hacker or app developer can build.
6Do not brainstorm new ideas.
7Use only the opportunity, evidence, pain points, ICP, and market signals provided.
8Your output must be practical enough to hand to a coding agent.
9Context:
10[PASTE KIMI RESEARCH OUTPUT HERE]
11Build the PRD with the following structure:
121. Product Summary
13- What are we building?
14- Who is it for?
15- What painful workflow does it remove?
16- Why would someone pay for it?
172. ICP
18- Exact customer type
19- Company size
20- Role/title of buyer
21- Role/title of daily user
22- Current tools they use
23- Current workaround
24- Budget assumptions
25- Buying trigger
263. Pain Point
27- Exact problem
28- Why it is painful
29- How often it happens
30- What it costs in time/money
31- What happens if it is not solved
32- Evidence from research
334. Existing Alternatives
34- Current software options
35- Manual workarounds
36- Spreadsheets
37- WhatsApp/email workflows
38- Agencies or human labor
39- Why each alternative fails
405. Product Positioning
41- One-line positioning
42- Homepage headline
43- Subheadline
44- Primary promise
45- Main objection
46- Why now
476. Core Workflow
48Describe the main user journey step by step.
49Example:
501. User signs up
512. User connects/imports data
523. AI analyzes workflow
534. User reviews suggestions
545. System generates output
556. User approves/sends/exports
567. System tracks status
57Make this specific to the opportunity.
587. MVP Feature Scope
59Separate into:
60Must have:
61- Features required for the product to work
62Should have:
63- Useful but not required for v1
64Do NOT build:
65- Features that would slow down launch
66- Nice-to-have dashboards
67- Complex integrations
68- Enterprise features
69- Anything not needed for first 10 customers
708. User Stories
71Write user stories in this format:
72As a [user],
73I want to [action],
74so that [outcome].
75Include at least:
76- onboarding stories
77- core workflow stories
78- admin stories
79- billing stories
80- error/edge case stories
819. Data Model
82Design the database schema.
83Include:
84- tables
85- fields
86- relationships
87- important indexes
88- status enums
89- audit/logging needs
90Keep it MVP-friendly.
9110. Pages and Screens
92List every required screen:
93- landing page
94- signup/login
95- onboarding
96- dashboard
97- main workflow page
98- detail page
99- settings
100- billing/pricing
101- empty states
102- error states
103For each screen, describe:
104- purpose
105- main components
106- primary CTA
107- data shown
108- empty state
10911. API / Backend Requirements
110List:
111- API routes
112- background jobs
113- third-party services
114- file uploads if needed
115- AI calls if needed
116- scheduled tasks if needed
11712. AI Features
118If AI is used, define:
119- exact AI task
120- input
121- output
122- prompt behavior
123- guardrails
124- human review step
125- failure handling
126Do not add AI unless it clearly improves the workflow.
12713. Pricing
128Recommend:
129- free trial or not
130- pricing tiers
131- first paid plan
132- value metric
133- why the customer would pay
134- what price to test first
13514. 2-Week Build Plan
136Break the MVP into 10 working days.
137For each day:
138- goal
139- features to build
140- files/modules likely needed
141- acceptance criteria
14215. Launch Plan
143First 10 customers:
144- who to contact
145- where to find them
146- exact outreach angle
147- what demo to show
148- what offer to make
14916. Risks
150List:
151- product risks
152- technical risks
153- distribution risks
154- willingness-to-pay risks
155- data quality risks
156For each risk, give a mitigation.
15717. Success Metrics
158Define:
159- activation metric
160- usage metric
161- retention signal
162- revenue signal
163- first-week success criteria
16418. Final Build Brief for Kimi
165End with a concise build brief that can be pasted into Kimi Code.
166It should include:
167- product goal
168- tech stack recommendation
169- MVP scope
170- pages
171- database
172- APIs
173- implementation order
174- what not to build
175Important rules:
176- Be specific.
177- Keep scope small.
178- Optimize for shipping in 2 weeks.
179- Do not write vague startup advice.
180- Do not add unnecessary features.
181- Think like a product operator who wants revenue fast.

8. What the PRD Must Include

Do not ask Claude for a vague product idea.

Ask for a real PRD.

The PRD should include:

→ product positioning

→ target customer

→ painful workflow

→ user stories

→ feature priorities

→ database schema

→ dashboard structure

→ onboarding flow

→ pricing model

→ MVP scope

→ edge cases

→ success metrics

→ what NOT to build

That last part matters.

What NOT to build saves more time than what to build.

Most MVPs die from extra features.

Claude is good at saying:

"This is not needed for version one."

That is why you use it here.

Not because it writes better buttons.

Because it thinks better.

PART 4: DESIGN BEFORE BUILDING

(Give the coding model a visual target)

9. Use ChatGPT for Visual Assets

After the PRD is done, generate the visual layer.

Use ChatGPT for:

→ app icons

→ dashboard illustrations

→ empty states

→ onboarding graphics

→ landing page visuals

→ feature images

→ small UI icons

Most indie hackers ship ugly products because design slows them down.

But you do not need perfect design on day one.

You need a direction.

Visual assets make the product feel real before the backend is even finished.

They also help the coding model understand the tone.

Is this a clinic tool?

A real estate dashboard?

A warehouse operations system?

A lead generation machine?

Visual direction changes the output.

10. Use Google Stitch for UI

Then use Google Stitch.

Give it the PRD.

Ask it to design the product screens.

You want:

→ dashboard

→ onboarding

→ main workflow

→ settings

→ pricing page

→ empty states

→ mobile screens

This gives Kimi a visual target.

That matters.

If you tell an AI coding agent:

"Make a nice dashboard."

You get the same generic SaaS UI everyone gets.

But if you give it:

→ PRD

→ UI screens

→ assets

→ workflow

Now it can build something much closer to a real product.

Design first.

Build second.

PART 5: BUILD CHEAP WITH KIMI K2.6

(Use cheap tokens for the messy execution loop)

11. Kimi Is the Builder

Now bring Kimi back.

This time for execution.

Give it:

→ Claude PRD

→ Stitch UI screens

→ ChatGPT assets

→ tech stack

→ folder structure

→ database schema

→ implementation plan

Then let it build.

Use Kimi for:

→ scaffolding

→ CRUD

→ auth

→ dashboards

→ API routes

→ database models

→ background jobs

→ styling fixes

→ refactors

→ tests

This is where cheap tokens matter.

Building is not one clean prompt.

Building is:

Prompt.

Run.

Error.

Fix.

Run again.

Change scope.

Fix styling.

Refactor.

Test.

Ship.

You do not want to burn Claude Opus limits doing that.

Use Kimi for the messy middle.

12. Claude Comes Back as the Reviewer

After Kimi builds, bring Claude back.

Not to rewrite the whole app.

To review it.

Ask Claude:

→ Does this match the PRD?

→ What is missing?

→ What will confuse users?

→ What should be removed?

→ What is risky?

→ What will break in production?

→ What should we fix before launch?

This is where Claude is valuable again.

High-level review.

Product judgment.

Architecture sanity check.

Claude should inspect the product like a senior engineer + product manager.

Not like a code generator.

PART 6: THE COMPLETE WORKFLOW

(One person operating like a product team)

13. The Full Software Factory

Here is the full workflow:

Kimi Agent Swarm → research opportunities

Claude Opus 4.8 → write the PRD

ChatGPT → generate visuals and assets

Google Stitch → design the UI

Kimi K2.6 → build the MVP cheaply

Claude Opus 4.8 → review the final product

That is the software factory.

One person.

Multiple models.

Each model doing the job it is actually good at.

The old way:

One AI model does everything badly.

The new way:

Research agent.

Product manager.

Designer.

Builder.

Reviewer.

All inside one workflow.

Most people are still asking AI:

"Build me an app."

The builders who win will ask:

"Which model should do which job?"

14. The Exact Prompt Stack

Use this stack:

Kimi Research Prompt

"Act as an autonomous startup opportunity discovery swarm.

Spawn research agents across Reddit, G2, Capterra, reviews, forums, LinkedIn, job posts, and competitor sites.

Find 100 evidence-backed opportunities.

Reject weak ideas.

Rank the top 25 by pain, willingness to pay, distribution, AI leverage, and speed to revenue."

Claude PRD Prompt

"Take this opportunity research and write a complete PRD.

Include ICP, pain point, product positioning, core workflows, MVP scope, user stories, database schema, pricing model, launch plan, edge cases, and what NOT to build."

ChatGPT Asset Prompt

"Create visual direction for this product.

Generate prompts for app icon, dashboard illustration, empty states, onboarding graphics, landing page visuals, and small UI icons."

Google Stitch Prompt

"Design the core product UI from this PRD.

Create dashboard, onboarding, main workflow, settings, pricing, empty states, and mobile responsive screens."

Kimi Build Prompt

"Build this MVP from the PRD, UI direction, assets, database schema, and implementation plan.

Prioritize working product over extra features.

Implement step by step.

Run tests.

Fix errors.

Keep scope tight."

This is not magic.

It is operations.

AI is not replacing software teams with one chatbot.

It is turning one builder into the operator of a small software factory.

FINAL FRAMEWORK

If you remember one thing, remember this:

Claude Opus 4.8 is not your cheap coding worker.

It is your architect.

Kimi is not just a Claude alternative.

It is your research swarm and build engine.

ChatGPT is your visual asset generator.

Google Stitch is your UI designer.

Together, they form a workflow:

Research → PRD → Design → Build → Review

That is how you stop vibe coding.

That is how you build faster.

That is how one indie hacker can operate like a product team.

The future is not one AI model doing everything.

The future is knowing how to route the work.

Save this workflow.

You will use it for your next MVP.