AI SDLC Advisory

Move from AI-assisted coding to agentic product delivery.

We help engineering organizations build a delivery system where agents move product work through the full SDLC, while people set direction, review critical decisions, and retain control. Start with one pilot team, prove the model, then scale what works.

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Trusted by 100+ Enterprise clients

Why redesign the SDLC

Turn individual AI gains into team results.

We redesign how product intent, context, implementation, verification, and release work together, then prove the new delivery loop with one team before scaling it.

  • Connect the full lifecycle.

    Product intent, design, implementation, validation, release, and feedback operate as one delivery loop.

  • Keep people accountable.

    Teams set direction, review critical decisions, and define the controls agents must follow.

  • Own the system behind the agents.

    Context, skills, integrations, and guardrails live in your environment instead of depending on one vendor.

  • Scale evidence, not experiments.

    Prove the model with one team, measure the result, then expand what works.

Services

Build the agentic delivery loop.

  • Use Cases

  • AI SDLC Assessment & Roadmap

    Map the current SDLC, identify where agents can remove delivery bottlenecks, and define the roadmap and pilot.

  • Agent Skills & Context Engineering

    Turn company playbooks, engineering standards, and repository context into versioned, tested instructions that agents can reliably execute.

  • SDLC Automation

    Connect product context, implementation, verification, and release so agents can move work across lifecycle boundaries with clear controls.

  • Agentic Engineering Transformation

    Launch the operating model in real delivery, with the context, skills, roles, and practices teams need to own and scale it.

  • Figma-to-Code Workflows

    Turn approved Figma designs and design-system components into usable UI code, with engineers reviewing quality, architecture, and native feel.

  • Adoption Measurement

    Measure how agentic workflows affect delivery speed, quality, and adoption before scaling them across the SDLC.

AI SDLC Advisory

Build your first agentic delivery loop.

Start with one team and one real workflow. We will assess the current lifecycle, design the target loop, and define the pilot that proves what should scale.

Build the first loop

Scope → Build → Scale

Assess, prove, and scale agentic delivery.

  • Scope

    We select a product workflow, define where agents act, and agree the controls and success measures.

    • Workflow and owners defined
    • Baseline and controls agreed
    • Token budgets confirmed

  • Build

    We connect context, agents, and verification to your tools, then run the workflow on your product backlog.

    • Running on your product backlog
    • Speed and quality measured
    • Business impact validated

  • Scale

    We document the workflow, transfer ownership, and extend it across teams and products based on results.

    • Your team owns the workflow
    • Expand based on results
    • Full knowledge handover
3x
Delivery acceleration
80%
Effort executed by agents
Industry runs on our tooling
50M+
OSS downloads / month
Built on Agent Device.
100+
Enterprise projects delivered
React Foundation Founding Member
300+ commits to React Native
~6x
Faster prototyping
60+
Components mapped with full coverage

10 years of React Native → Now in your AI stack

Build your first agentic delivery loop.

Start with one team and one real workflow. We will assess the current lifecycle, design the target loop, and define the pilot that proves what should scale.

Build the first loop

Open Source

Build with our open-source tools.

We open-source the tools behind our delivery model.
Use them, fork them, or let us run them for you.

Check All Tools

Agent Skills

Callstack’s best practices on React Native performance optimization, upgrading, CI workflows, and brownfield migrations

1.7K stars

Agent Device

CLI to control iOS and Android devices for AI agents

980.4K downloads/mo

Apex

Agentic coding model for mobile and web

Agent React DevTools

Gives AI agents access to React DevTools

251 stars

Insights

Worth your time, by engineers.

Explore Insights
Building the React Native Software Factory — cover

Nov 11Talk

Building the React Native Software Factory

Join us at React Foundation Meetup London on November 11 to explore how AI agents build and debug React Native apps, from one terminal to the cloud.

Building a Software Factory: Write Specs an Agent Can Build From — cover

Nov 6Article

Building a Software Factory: Write Specs an Agent Can Build From

Szymon Chmal uses a Simlock device-cleanup feature to explain how he plans work for coding agents. Follow the process from code research and product decisions to testable tasks, independent specification checks, and human approval.

Large-Scale Migrations With Coding Agents: Planning, Verification, and Rollback — cover

Nov 4Article

Large-Scale Migrations With Coding Agents: Planning, Verification, and Rollback

Organize a large-scale codebase migration around documented requirements, scoped agent tasks, and human review. This article covers verification, telemetry, staged rollout, and rollback criteria.

Building a Software Factory: The Night My Agents Waited for Me — cover

Oct 28Article

Building a Software Factory: The Night My Agents Waited for Me

Two coding agents worked overnight on Simlock and ended up waiting for their maintainer. This article examines the questions that stopped them and the workflow changes that followed, from recurring permissions and review limits to product choices agents can make provisionally for human review.

Your AI Coding Agent Still Needs an Architecture — cover

Oct 22Article

Your AI Coding Agent Still Needs an Architecture

AI coding agents make implementation decisions about logic, dependencies, and shared behavior. A favorites feature illustrates how explicit contracts, gradual migration, behavior tests, and automated dependency checks give engineers a basis for reviewing those decisions.

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Oct 15Live Stream

Who Left the Agents Running? React Native Software Factories

Join Kewin Wereszczyński and Szymon Chmal to explore what can go wrong in a React Native software factory overnight and the controls that keep agents on track.

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Oct 14Podcast

When Coding Gets Faster, What Breaks Next?

Matt Hargett explains how AI moves bottlenecks across testing, deployment, infrastructure, support, and the rest of software delivery.

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Oct 12Podcast

AI Agent Observability With Ivana Huckova and Sven Großmann

Grafana's Ivana Huckova and Sven Großmann discuss AI agent observability, coding-agent costs, PR analytics, secret redaction, and local guardrails.