DevDay Pune

Software Engineering in the Age of AI

Sat, Oct 24 · 10:00 AM IST

Business Bay, Golf Course Square, Airport Rd, Jayprakash Nagar, Yerawada, Pune, Maharashtra 411006, India, Pune, MH, IN

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Software Engineering in the Age of AI

Topic 1: A Green Harness Is Not a Healthy Harness
Instrumenting your coding agent’s harness against silent failure

Most teams that build a coding-agent harness (a CLAUDE .md, a few hooks, a CI gate) treat it as config they set once. It isn’t. The harness is supposed to guard your code changes. Those same changes erode the harness itself: the standing-rules file goes stale until it’s confidently wrong rather than usefully absent, rule density crosses an adherence cliff where even frontier models stop following it, and the agent doing the work can satisfy a failing gate by deleting the test that enforces it. Nobody’s watching the watcher, and a harness that fails silently is worse than no harness at all.

This talk gives you a failure taxonomy for the harness itself and the safety net for each failure. The core distinction: encoded guardrails (lint, tests, static analysis, anything the agent doing the work can edit or delete) versus structural guardrails (permission hooks the agent’s own session can’t switch off, default-deny network egress, a CI gate with no admin-bypass path). The first kind only holds if the agent cooperates; the second holds regardless of what the agent tries. “Coverage is theater” generalizes: every encoded guardrail is theater against a suggestible actor.

From there, three concrete practices for treating the harness as production infrastructure rather than settings: config-drift detection in CI, canary load-lines that confirm context actually loaded, and harness regression evals that gate every change to a prompt, tool description, or iteration cap before it ships.

Pre-requisites for attendees
Engineers and teams running coding agents against real production codebases who’ve already written a CLAUDE.md/AGENTS.md or a hook and want to know whether it’s actually holding. Includes people building agent infrastructure, harness tooling, and evaluation frameworks.
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Topic 2: The Hourglass-Shaped SDLC
Most software teams still organise delivery around implementation. Estimates are often driven by the expected complexity of the implementation, progress is measured through the development stage, and testing and review wait for the implementation to finish.

That arrangement made sense. Implementation consumed most of the effort needed to turn an idea into working software. Building also forced the design to meet the codebase and change under pressure.

AI changes the balance by reducing the human attention spent on implementation. Work around implementation continues to consume substantial human attention. Teams still define the problem and choose a direction before code is written. After code exists, somebody has to decide whether the result is correct, useful, and safe to release.

If the width of each stage represents its share of human attention, the SDLC starts to look like an hourglass. Adding a faster coding tool to the old workflow accelerates the part already taking less human time, while decisions and evidence continue to set the pace for software delivery.

Software output can then rise faster than confidence, which is why this talk argues for an SDLC organised around decisions before implementation, evidence after implementation, and learning that carries production feedback into the next change.

Meet the Speakers
Karun Japhet
Solution Consultant, Sahaj Software
Karun is an engineer and consultant at Sahaj Software. I work on large-scale systems, architecture, and AI in software development. Most of my time goes into helping teams design systems that hold up as they grow especially as AI becomes part of how we build.

Sujit Kamthe
Solution Consultant, Sahaj Software
Sujit is an engineering leader, software architect and AI practitioner with more than 16 years of experience building distributed systems, cloud platforms and enterprise applications, and building high performing engineering teams. His current work focuses on production-grade agentic AI, cloud-native architecture and AI-assisted software engineering. He writes and speaks about software architecture, engineering practices, developer productivity and the changing role of engineers.

Agenda

• 10:00 AM – 10:15 AM: Entry & Networking
• 10:15 AM – 11:15 AM: Talk 1 – A Green Harness Is Not a Healthy Harness
• 11:15 AM – 11:30 AM: Coffee Break & Networking
• 11:30 AM – 12:30 PM: Talk 2 – The Hourglass-Shaped SDLC
• 12:30 PM onwards: Networking

Entry to the event will close at 10:30 AM.

🎟️ Please RSVP here to join-in for this conversation in-person.