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Kiberon LabsAgentic Engineering Ebook

Collaborative Development Structure

Description

Section titled “Description”

Agentic software development should preserve the strong coordination patterns of human teams instead of bypassing them. The right target is not fewer engineering rituals, but more scalable versions of them with agents preparing material, participating in discussion, and executing follow-up work.

Mimic Mature Team Behavior

Section titled “Mimic Mature Team Behavior”

Healthy engineering organizations rely on shared structures because large changes require alignment, prioritization, and review. A fully agentic system should therefore reproduce and expand patterns such as:

  • Architecture discussions for high-impact design decisions.
  • Estimation or pokering sessions to expose uncertainty and scope risk.
  • Issue tracking that preserves intent, dependencies, and ownership.
  • Review structures that separate implementation from approval.
  • Retrospectives and incident follow-up when delivery quality slips.

The expansion comes from preparation and continuity. Agents can gather prior art, propose trade-offs, draft RFCs, decompose epics, generate test plans, and keep issue state synchronized across sessions. Humans still decide where judgment is needed, but they no longer need to manually assemble every artifact from scratch.

Architecture and Estimation

Section titled “Architecture and Estimation”

Architecture meetings remain valuable because they compress multiple perspectives into a single decision point. Agents can make those meetings stronger by drafting diagrams, collecting affected code paths, identifying migration hazards, and producing alternative designs before humans meet.

Estimation also survives in an agentic system, but the output becomes more operational. Instead of only assigning story points, the system can estimate execution cost, review load, model class, expected test depth, and whether the work should be split before coding begins.

Issue Tracking As Shared Memory

Section titled “Issue Tracking As Shared Memory”

Issues become the durable interface between humans and agents. They should capture:

  • Problem statement and business intent.
  • Architectural constraints and interfaces.
  • Acceptance criteria and test expectations.
  • Linked plans, review comments, and deployment notes.
  • Rework history when execution loops back.

Collaborative issue creation matters here. Humans may open an issue from a conversation or voice note, and agents can refine it into a clearer artifact without erasing the original intent.

Review Structures and Engineering Discipline

Section titled “Review Structures and Engineering Discipline”

Code review should continue to act as a boundary between implementation and acceptance, even if agents produce most changes. Review can itself be multi-stage: automated checks, agent critique, human review, and policy approval for sensitive changes.

TDD and DDD still matter in this world. TDD gives the system an executable boundary for behavior before and during implementation. DDD gives it a language for identifying bounded contexts, aggregates, invariants, and ownership boundaries that should survive both human and autonomous change.

Section titled “Related Concepts”