Agile gave us structure, but startups are now exploring agentic workflows where AI contributes directly to planning, estimation, and execution. Core practices like backlog grooming, story pointing, and burndown tracking are being reimagined — with agents assisting, suggesting, and sometimes completing tasks. This shift isn’t just about speed, but about redefining how teams work and who’s doing the work.

Agile brought structure to software teams: roles, rituals, and rhythm. But with AI agents entering the picture, startups are starting to question — do we still need to do it all manually?

This post explores how the shift is playing out in the trenches and I am trying to get data points from others to inform decision making.

Enterprises still rely on Agile: predictable sprints, well-defined roles, and recurring ceremonies.

Startups are experimenting: AI agents triage backlogs, suggest story points, and contribute to burndown — not just code.

Here’s how 3 core practices are evolving.

𝘽𝙖𝙘𝙠𝙡𝙤𝙜 𝙂𝙧𝙤𝙤𝙢𝙞𝙣𝙜 THEN - Agile - Enterprises:

  • PMs + teams groom tickets manually in weekly meetings. NOW - Agentic - Startups:
  • Agents auto-triage feedback and logs into structured backlog items — complete with labels and draft criteria.
  • Humans review, not rewrite.

𝙎𝙩𝙤𝙧𝙮 𝙋𝙤𝙞𝙣𝙩𝙞𝙣𝙜 THEN - Agile - Enterprises:

  • Planning poker. Gut-feel estimates based on prior sprints. Time-consuming and subjective.

NOW - Agentic - Startups:

  • Agents propose points based on code patterns, historical data, and dependency analysis.
  • Engineers calibrate — faster, less biased.

𝘽𝙪𝙧𝙣𝙙𝙤𝙬𝙣 𝘾𝙝𝙖𝙧𝙩𝙨 THEN - Agile - Enterprises:

  • Charts track only human effort. NOW - Agentic - Startups:
  • Burndown includes agent contributions: test coverage, docs, security scans.
  • Teams see the whole picture, not just ticket closes.

Where are you on this spectrum?

  • Agile (Human-centered workflows)
  • Agentic (Agents actively contribute)
  • Hybrid (Human + Agent collaboration)
  • Still figuring it out