From Code Suggestions to Agentic Software Development
AI agents in software development are specialised autonomous systems that collaborate across planning, building, testing, and deployment stages of the software development lifecycle, turning natural‑language intent into working applications while keeping humans accountable for decisions and quality. This marks a clear break from earlier tools that focused on completing single lines or small blocks of code. According to Forrester’s State of Agentic Software Development, generative AI has crossed a threshold where agents now coordinate analysis, design, implementation, tests, and release activities as an automated SDLC pipeline. Instead of treating AI as a sidekick inside an IDE, teams delegate goals such as “build this feature” and let agentic software delivery orchestrate decomposing work, generating artifacts, and preparing releases. Individual productivity boosts from coding assistants matter less than the compounding gains unlocked when all major lifecycle steps are automated in a coherent way.
Endava’s Network of Specialised Agents Replaces the Old Fullstack
Endava offers a concrete example of agentic software delivery in production. The company is building a network of specialised AI agents on a unified platform that combines ChatGPT Enterprise with Codex models, assigning each agent full ownership of a specific development stage. One agent turns raw business requirements into clear user stories and functional specifications, another generates boilerplate logic, runs unit tests, and drafts documentation, while a separate review agent scans pull requests for vulnerabilities and formatting issues before any human is asked to review. Teams compose these agents into modular workflows: a web application pipeline can chain frontend, API testing, and accessibility agents, while data teams connect agents for pipeline construction, schema validation, and performance tuning. This modular, agent‑orchestrated approach replaces the monolithic “fullstack engineer” workflow with a flexible automated SDLC pipeline tuned to each project’s constraints and goals.
Engineers Become Orchestrators of Agent Experience
As AI agents take over more execution work, the engineer’s value shifts from typing code to designing and supervising agent experience. Netlify CTO Dana Lawson argues that writing code was always less than a quarter of the job, and that engineers remain “the shepherd of production,” making sure inputs, outputs, and risks are well understood. In this model, agent orchestration engineering is a core skill: deciding which agents to use, how they exchange signals, and where human review must remain. Agent experience blends developer and user experience concerns, defining how humans and agents collaborate, not only how APIs are called. Netlify’s own platform redesign to support both AI agents and citizen “builders” showed that clearer agent‑oriented error messages and machine‑friendly build outputs also improve traditional developer experience, revealing how thoughtful agent experience design raises quality for every participant in the delivery process.
A Billion New Apps and the Future of the SDLC
Agentic software development is also widening who can build software. Agentic AI turns intent, expressed in conversational language, into the new programming interface, opening software creation to people who do not know Git or formal programming concepts. Dana Lawson predicts there will be a billion new applications written by 2029 as AI agents remove human bandwidth as the limiting factor and support a new population of “builders.” Forrester notes that without end‑to‑end AI adoption, coding speed gains of 30% to 40% translate into less than 10% overall productivity because planning, testing, and release remain bottlenecks. With orchestrated agents spanning the SDLC, these limits start to disappear. Engineers will focus more on outcome engineering: deciding what not to build, where automation should stop, and how to keep automated SDLC pipelines reliable, safe, and aligned with real business value.
