SatoriXR
AI-assisted delivery got faster and the constraint moved to deciding. They hired a second product manager, not a third developer. The strategy and roadmap in Feature1 became the queue the developers pull from.
AI SDLC
Adopt the AI SDLC without disrupting your team
Agents build, humans verify, and the intent comes from your product strategy. Feature1 runs the lifecycle from decision to shipped feature, with the people and tools you already have.
The AI software development lifecycle (AI SDLC, or AI-native SDLC) moves the expensive work to the front: deciding what should exist, writing acceptance criteria that say what done means, and verifying what the agent built. Most write-ups start at the repository with the intent already written. Feature1 is the layer that produces the intent, holds it, and hands it to Claude Code, Codex or Cursor over MCP.
The POC: your PM, your developer, read-only GitHub access, two features shipped through the AI SDLC in one to two weeks.
Sound familiar?
- Your developers use AI. The business is not seeing the benefit.
- AI ships features fast, and a lot of unintended changes with them.
- Shipping got faster. Which metric moved?
- You want to run Anthropic's AI-native SDLC playbook, without the trouble teams report in week two.
- Every "AI SDLC" diagram starts with intent already written. Yours does not say where it comes from.
- You want to adopt it without a reorg, a course, or a long learning curve for the developers.
The AI SDLC, with the step the playbooks skip
What the lifecycle gets right
- Code is generated, so writing it is no longer the slow step.
- Intent is written down first, as a spec and acceptance criteria.
- The agent builds from the intent; a person reviews and ships.
- Mistakes got cheap to make and stayed expensive to find, so verification is the job.
What it leaves open
- Where the intent comes from: which customer, which goal, which capability.
- What the product can already do, so the agent does not rebuild it.
- Which of the twenty backlog items is next, and why.
- What adoption and error signals say after the feature ships.
Feature1 closes that loop: strategy, product reality, roadmap, features with acceptance criteria, the agent building from them over MCP, and the picture of the product updating when the code changes. We wrote the long version in The AI-native SDLC, with the part it leaves out.
How the lifecycle runs in Feature1
Strategy
A one-page product strategy narrative, written in Feature1 from your business goals, customers and competitors.
Product reality
A read-only scan of the repository keeps a current picture of what the product can do.
Roadmap
The gap between strategy and product, as initiatives with an objective and a measure each.
Features and acceptance criteria
Each initiative planned into features and stories with criteria, before any code. This is the intent the lifecycle starts from.
Agents build
Claude Code, Codex or Cursor reads the criteria over MCP and builds. Your developer owns the pull request.
Results feed the next decision
The capability picture updates on merge. Adoption and error signals from your analytics and monitoring inform what comes next.
What it looked like in three teams
Quantem
A junior developer built an MCP layer in one day from written acceptance criteria and it passed end-to-end testing. The context work took four to five days; the build took one.
Jarshare
A Replit store with one unintegrated server file became a real product once its capabilities were written down and the next features were specified against them.
Paid proof of concept
Run the AI SDLC on two real features. $500.
A fixed-scope proof of concept with your own PM and developer. You see the lifecycle working on your product, with your coding agent, before you change anything else.
You give
- One product manager, or the founder who decides what gets built
- One developer with a coding agent (Claude Code, Codex or Cursor)
- GitHub access, read-only. Feature1 reads the repository and never writes to it
- An NDA, signed before anything is read
You get, in one to two weeks
- A one-page product strategy narrative
- A roadmap built on what the product can already do
- Two features shipped by your developer and their agent, from acceptance criteria held in Feature1 and read over MCP
- Your team working spec-first, without a course or a migration
$500Flat. Paid once the scope is agreed on the call.Book the POC callOr sign up and start on your own, free
Abdulrahman, founder of Feature1, runs the POC with your team. He does not write the code. Your developer does, with the agent, which is the point: the process has to work with the people you have.
Questions people ask
What is the AI SDLC?
A software development lifecycle in which coding agents generate the code from written intent and people decide what should exist, write the acceptance criteria, and verify what was built. The old steps got faster and moved to the front; they did not become optional.
How is it different from adding Copilot or Cursor to the team?
An assistant speeds up typing inside the old lifecycle. The AI SDLC changes the order of work: intent and acceptance criteria first, generation second, verification as the developer's main job. Without the first step, faster typing produces more unintended change.
Do we need to change our tools?
No. GitHub, GitLab or Bitbucket stay. Claude Code, Codex or Cursor stay. Feature1 adds the layer above them that holds the strategy, the roadmap and the acceptance criteria, and exposes it over MCP.
Does this follow Anthropic's AI-native SDLC playbook?
It follows the same shape: intent written first, agents build, humans verify. Feature1 supplies the step the playbook starts after, which is where the intent comes from and how it stays current as the product changes.
What is in the $500 POC?
One to two weeks with your PM and one developer: a product strategy narrative, a roadmap built on what the product already does, and two features shipped from acceptance criteria held in Feature1. NDA first, read-only GitHub access, your developer writes the code with their agent.
Is there a free way to start?
Yes. Sign up, no credit card, and write the first Product Strategy Narrative yourself. The POC is for teams that want the lifecycle set up with them, on their product, in a fixed window.
Give your agents intent worth building from.
Two features, your team, one to two weeks. Or sign up and write the first narrative yourself, free.