Engagements · 6 ways to work with Loop

The shape of the engagement matches where you are.

From a single embedded engineer to a 6–10 week transformation sprint. Every offer is built around one belief: the future of QA leadership is not owning test execution. It's owning the quality intelligence layer that helps engineering ship with confidence.

01Diagnosis

An audit that names where leverage is leaking.

02Alignment

A workshop that gets QA, engineering, and product on one model.

03Transformation

A sprint that ships the new operating model with measurable ROI.

Section 01 · People

Loop SDETs and the hiring function around them.

Three ways to put senior, AI-fluent quality engineers inside your team. Embedded, screened, or recruited.

PPL-001People

Embedded QA

A senior SDET on your team, beachheading AI-native quality.

Buyer state. “We need someone who can show our team what AI-augmented testing actually looks like.”

Loop's embedded QA engineers join your team as full members. Not contractors who throw deliverables over a wall. They're senior SDETs who understand augmented coding and AI deeply, and their job is to prove the new operating model by living it: shipping leverage every week, mentoring teammates into the practice, and turning the hiring profile of QA inside your org.

PPL-002People

Managed Hiring

Tech screenings for companies who don't yet know how to hire for AI.

Buyer state. “I have headcount, but I don't trust our pipeline to assess AI fluency.”

Most engineering orgs haven't yet retooled their interview loop for AI-augmented work. Loop runs the entire screening process. Coding interview design, technical screens, take-homes, debrief calibration. For QA and engineering hires where AI fluency, system thinking, and quality intuition all matter. You see only the candidates who pass our bar.

PPL-003People

Traditional Recruitment

Direct candidate placement at a standard recruiting fee.

Buyer state. “I just need qualified QA / engineering candidates.”

If you'd rather skip the screening engagement and just see qualified candidates, Loop also runs traditional recruiting on a standard per-placement fee. Same talent pool, same quality bar. Just a leaner contract structure for teams that already know how to interview.

Section 02 · Engagements

Diagnosis, alignment, and transformation.

Three engagement shapes for QA leaders moving from “what do I do?” to “how do we actually change?”

AUD-001Audit

QA Leverage Review

A one-day private review of your QA team, process, automation, dashboards, and constraints. Through a leverage lens.

Buyer state. “I need a clear, outside diagnosis of our current QA setup before we buy more tools, reorganize the team, or expand automation.”

Not a generic workshop. The day is built around your current QA reality. Your people, your access, your automation, your dashboards, your team's skills, and the constraints you're operating under. Pre-work intake → curated agenda → one-day private review → takeaway packet with a 90-day plan and a boss-ready summary memo.

ALN-001Alignment

Quality Strategy & Leadership Alignment

A 3–6 week leadership engagement to align QA, engineering, product, and executives around how quality should work in the AI era.

Buyer state. “We know QA needs to change, but the change can't be made by the QA leader alone.”

Not a training day. A leadership engagement that begins with a private current-state diagnosis (intake + optional stakeholder interviews), runs a one-day core session that aligns QA, engineering, product, and executive leadership on the future operating model, and follows with three 90-minute progress reviews so the strategy turns into operating change.

SPR-001Sprint

Quality Transformation Sprint

A 6–10 week implementation sprint where we work alongside your team to move QA from test execution to a higher-leverage quality operating model.

Buyer state. “We know the current QA model isn't creating enough leverage. We need hands-on help changing it. Not another strategy session.”

Not another strategy session. Over 6–10 weeks we work alongside your QA, engineering, product, and leadership teams to change how quality actually happens. Review real QA work, redesign ownership, ship an AI/automation pilot, build the dashboard, and establish the management cadence that makes the new model stick.

Track record

Last year of engagements, in numbers.

30+

Engagements shipped

94%

On-time releases

−42%

Avg. regression CI minutes

Critical escapes (last 12 mo)

Numbers reflect engagements where Loop ran the operating-model reset or the transformation sprint. See the client roster for the full case set.

From past engagements

What clients say about working with Loop.

“The audit told me three things I'd been missing. Worth it before I argued for headcount.”

. SarahQA Director at

Series-B fintech · ~50 engineers

Engagement: QA Leverage Review

“The reset workshop got our VP of Eng on the same page as QA. The 90-day plan we left with is now policy.”

. MarcusHead of Quality at

Healthcare SaaS · 120 engineers

Engagement: Quality Strategy & Leadership Alignment

“The sprint shipped a regression-reduction pilot that reclaimed 22 engineering-hours per sprint. ROI was visible by week 6.”

. PriyaQA Director at

E-commerce platform · 200+ engineers

Engagement: Quality Transformation Sprint

Names + companies anonymized at the speakers' request.

Watch · Companion videos

Talks behind the engagements

Subscribe on YouTube · @benfellows-dev →

May 4, 2026

Inside a Real Agentic Pipeline (Step-by-Step Breakdown)

Agentic pipelines sound great in clean demos, but what do they actually look like in production? In this video, I break down one of the real AI development pipelines I use almost every day: how it starts from a prompt, creates its own branch and worktree, runs research, builds a plan, gets reviewed by a second agent, writes failing tests, implements until green, runs policy checks, and produces receipts at the end. I also cover what’s worked, what’s been over-engineered, where deterministic checks matter, and why “just run more agents in parallel” is not always the right answer. Sorry for the lower-energy video, I hadn’t eaten all day before recording this one 😅 Links: Newsletter: https://tinyideas.ai/#newsletters QA work at Loop: https://www.workwithloop.com/ LinkedIn: https://www.linkedin.com/in/ben-f-44778426/ X: https://x.com/FellowsBen

Watch on YouTube →

May 1, 2026

Are Agentic Pipelines Actually Worth It?

Are agentic pipelines actually worth the extra time, tokens, and complexity? My honest answer: it depends. Agentic pipelines can improve accuracy, visibility, governance, and control, but they also add real cost. They often take longer to run, use more tokens, introduce more orchestration, and create another layer of abstraction around your development process. So the question is not “do pipelines work?” The better question is: did this pipeline earn its cost? In this video, I walk through the framework I’m using to evaluate whether an agentic pipeline is actually worth running. That includes measuring the pipeline tax, tracking run receipts, comparing quality improvements, and using a ledger system to understand whether a pipeline is making the work better or just making it more complicated. I also share an example of a pipeline that looked good on paper but probably wasn’t worth it in practice. That’s an important part of the lesson: not every task needs a pipeline. Sometimes a single Claude Code or Codex session, guided by a strong engineer, is enough. The goal is to use pipelines surgically. Start simple. Measure what happens. Add complexity only when the pipeline is solving a real problem. And when a pipeline gets too large, use the data to make it smaller. If you’re experimenting with agentic development, this video is about how to think about ROI, accuracy, governance, and cost before building complex AI workflows everywhere.

Watch on YouTube →

Apr 30, 2026

Stop Doing AI “Factory Work” - Own Your Agentic Pipeline #agenticai #agentic #agenticcoding #coding

Stop treating AI like factory work. Rigid, assembly-line workflows break down with complex codebases. Owning your agentic pipeline means customizing every step and refreshing context each time—leading to better accuracy, flexibility, and scalability where it actually matters. #agenticai #agentic #agenticcoding #coding

Watch on YouTube →

Not sure which one

Start with the public course or the audit.

The public course gives you the framework and a 90-day plan. The audit applies it to your team. Most clients move up the ladder from there.

See the public course Inquire about the audit