I submitted a theme proposal for the STeP-IN Summit 2026. Below is the theme I proposed, along with the abstract explaining why I believe it is the need of the hour.
To enable AI and Agents to truly help us across the SDLC, engineers and businesses must restructure and realign the way they work. This change is critical and necessary.
Simply introducing AI and Agents into an organization is not enough. Their adoption requires a cultural shift in the organization and a change in the way engineers work.
Unless this shift happens, AI and agents cannot effectively understand and respond to the context in which they are being used. This is what I am learning.
My theme proposal is not selected, but I congratulate the person whose proposal is chosen.
See you at STeP-IN 2026!
Theme
"Restructuring and Orchestrating Myself and Tests with AI and Agents"
Abstract
The AI solution and tooling is everywhere in the SDLC for an
engineer and business.
How do the AI and Agents influence the below factors in my work and organization?
- The confidence in release
- The confidence in code and tests generated and written with assistance
- The speed of release
- The cost of going wrong in production
For an engineer, using AI and Agents is about efficient
productivity and personal upskilling.
For an engineering leader it is about the velocity and displacement in
business. The same AI and Agents but the
two different expectations and interpretations!
To achieve, both the engineer and engineering leader have to
restructure and orchestrate themselves individually and as a team with AI and
Agentic solutions. If not, above
mentioned factors will get impacted and derail the delivery.
Anytime the answer to above said factors is not confident, then
incorporation of AI and Agentic solutions in SDLC is not working. Then, it is just bragging – do you know how
our engineers spend the whole day using AI to code, test and ship? That’s it. It is not serving the business and engineer.
This is where, this theme is critical and a need –
Restructuring and Orchestrating Myself and Tests with AI and Agents.
Most of us are using AI and Agents without asking,
- How it has impacted the releases cycle compared to last year?
- How confident and fast we are in coding and testing compared to last year?
- Has it cut down the time of testing and automation compared to last year?
If there is no confident answer, you know it – one has to
restructure and orchestrate the self with AI.
How to do it? The test
engineers, SDETs & engineering leaders to share and talk on how they are doing
it in their work and org.
I submitted this theme and abstract in March 2026.
ReplyDeleteWhy I say this -- If there is no confident answer, you know it – one has to restructure and orchestrate the self with AI.
ReplyDeleteAs of today, the AI and Agents solution available for consumption is a project or organization specific. The org, business and engineers have to tailor the available AI and Agents solution to their problem solving efficiency and constraints.
Unless, the engineers are building their own AI and Agents solution to the need of the project and product, one has to restructure and orchestrate self with AI, today. This is my experience and so far learning.
I see that the theme for STeP-IN 2026 has been selected. Congratulations to the person who proposed it.
ReplyDeleteYou can refer to the selected theme on this page: https://stepinsummit.stepinforum.org/
I am also copying it here so that it remains available on my blog, even if it is removed from the STeP-IN website next year.
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Theme & Abstract
Autonomous Testing with Agentic AI: Moving Toward Self-Driving Quality
For years, test automation has promised efficiency, yet much of the work remains manual—creating scripts, maintaining test suites, addressing flaky tests, and adapting to constantly evolving applications. As software systems grow in complexity, traditional automation approaches are reaching their limits.
Agentic AI is redefining the future of quality engineering by introducing intelligent, autonomous agents that actively participate across the Software Development Life Cycle (SDLC). Rather than simply executing predefined scripts, these AI-powered agents can analyze requirements, generate and optimize test cases, identify risks, adapt testing strategies based on application changes, and assist in defect investigation and resolution.
This theme explores the evolution from automation to autonomy through multi-agent testing ecosystems, where specialized AI agents collaborate as requirement analysts, test designers, execution managers, defect triagers, and quality advisors. Together, they enable a self-improving testing framework that continuously learns, adapts, and scales alongside modern development practices.
Join us as we examine how Agentic AI is accelerating the journey toward “self-driving quality”—a future where testing becomes more intelligent, proactive, and resilient, allowing quality professionals to focus on innovation, strategy, and delivering exceptional customer experiences.