Why we left Toptal for Devlyn after 6 months

This is a real story from a CTO at a $40M Series-B SaaS company. The names of the people involved are anonymised at his request; the numbers, the calendar, and the engagement pattern are exactly as he described them in a CXO peer call last quarter. The pattern is not specific to Toptal — it shows up across every senior-vetted marketplace at the same six-month mark. But Toptal was his vendor, and Toptal is the one I will name.

The opening: a clean Toptal hire in week one

The CTO had a genuine engineering capacity gap. His in-house team was four engineers including himself, the roadmap had ten engineers’ worth of work in the next two quarters, and the FTE pipeline was running at a dead heat — five months from offer to ramped engineer. The board wanted the platform shipped before next year’s renewal cycle. He posted a brief on Toptal on a Monday.

By Wednesday he had three matched candidates. By Friday he had interviewed two of them. The chosen engineer — a senior backend, eight years of PostgreSQL and Node.js experience, working out of a European time zone with strong English — started the following Monday. The match was clean. Toptal did exactly what Toptal markets it does. The CTO told me at the end of week one he was the most relieved he had been in three months.

The hourly rate was $95/hour. At forty hours a week, the burn was $15,200 a month. The CTO had budget approval through quarter-end and was prepared to renew if it worked.

Months one through three: the velocity that did not arrive

Here is where the pattern starts. The Toptal engineer was capable. The work he produced was technically sound. He hit standups; he reviewed PRs; he shipped his tickets.

But the team’s velocity did not change. The CTO had hired the equivalent of a fifth in-house engineer — and the team was now shipping at the pace of 5 ÷ 4 engineers’ historical output, which is roughly what you would expect when the bar of an additional senior engineer multiplies by team size. Linear in the engineer count.

The CTO’s roadmap math required a multiplier, not an addition. He had budgeted ten engineers’ worth of work into the quarter. He had four FTE plus one Toptal contractor. Five engineers shipping at five engineers’ pace was still half the roadmap.

He told me he tried to articulate this to his board in month three. The board’s response was: “Then hire more Toptal contractors.” He did. Two more matches by month four. Burn climbed to $42,000 a month. Velocity climbed roughly 3× by engineer count, which is what three more engineers should produce — but the roadmap multiplier he needed was still not happening.

The structural issue: marketplaces add headcount linearly. CXOs running a 2026 roadmap need velocity per engineer to compound. Toptal does not promise that. He had been buying linear addition expecting compounding.

Month five: the contractor churn problem

In month five the original Toptal engineer left for a higher rate at another platform. Toptal’s two-week trial replacement is real — but mid-engagement churn after the trial window is on the buyer’s calendar. The CTO posted a new brief, ran another match cycle, and onboarded a replacement — three calendar weeks of velocity loss, which compounded against an already-late roadmap.

In month six, one of the second-cohort Toptal contractors dropped to half-capacity citing a “scheduling conflict” — which the CTO suspects (correctly, in 2026 marketplace terms) meant a higher-paying engagement on the side. Another partial replacement cycle. Another two calendar weeks lost.

The math by end of month six:

• 11 calendar weeks of capacity loss to mid-engagement churn over six months.
• $42,000 × 6 = $252,000 in Toptal spend.
• Roadmap was 38% complete against a target of 50%.
• Board had asked twice in the last quarter why velocity was not compounding.

He had also been reading every weekly newsletter aimed at IT CXOs in 2026. The pattern across them was consistent: AI-augmented engineering pods were shipping 4× the historical pace at the same engineer count. He had filed it as marketing language. By month six he was open to the possibility that it was not.

The Devlyn discovery call

He booked a 30-minute Devlyn discovery call on a Tuesday. He brought his roadmap, his Toptal burn rate, and his quarter-end deliverables. The discovery call ended with a recommended pod composition: two senior engineers plus a part-time DevOps lead and a dedicated PM line, plus AI-augmented engineering as the workflow standard.

The proposed retainer was $9,800 a month. Against his then-current Toptal burn of $42,000, the line-by-line math was: same engineer count, one PM line included, AI-augmented workflow promise of 4× historical pace, replacement guarantee internal to the practice, no marketplace churn risk. Devlyn proposed a 3-day free trial against a real scoped task — same task he would have posted on Toptal that week.

The trial ran Friday through Monday. The pod returned a working implementation of a feature his Toptal team had been quoted at three weeks. The 3-day output was not theatre; it was the AI-augmented workflow operating as advertised.

He hired Tuesday. The pod was in his Slack and repos within 24 hours.

Want to see the model against your actual roadmap? Book a 30-minute Devlyn discovery call → — no contracts, no commitment.

What changed: months seven, eight, nine

The CTO ran his Toptal engagements out for two more weeks while the Devlyn pod ramped, then closed the Toptal contracts cleanly. By month eight the team’s shipping cadence had compressed: features the in-house-plus-Toptal team had been quoting at three weeks were landing in five to six days. The 4× compression was not against a single engineer’s output; it was against the team’s historical output for similar scopes.

The structural reason — described to him by the Devlyn pod lead in a one-hour kickoff — was that AI-augmented engineering is a workflow design, not a tool selection. Cursor and Copilot in the hands of a Toptal contractor produce a 1.2–1.5× velocity bump. The same tools embedded in a pod-level workflow with senior validation, automated review pipelines, integrated testing, and compressed-cycle as the practice standard produce 4×. The delta is the workflow, not the tools.

By month nine he had shipped the next-quarter roadmap. The board stopped asking why velocity was not compounding. He converted one of the Devlyn pod members to a permanent FTE through Remote.com’s EOR product — Devlyn handled the introduction, Remote.com handled the compliance machinery. The remaining pod stayed on retainer for the platform work.

The honest reckoning: when Toptal was still right

This is the part the case-study format usually skips. Toptal was not the wrong vendor in months one through three. The CTO had a single-contractor capacity gap. Toptal filled it cleanly. If his roadmap had been one engineer of work rather than six engineers of compounding velocity, the original Toptal engagement would have been correct and he would have renewed it.

The vendor became wrong when his problem changed. The problem was no longer “I need a senior contractor.” The problem was “I need pod-shaped delivery at AI-augmented velocity.” Toptal does not solve the second problem. Devlyn does.

The CTOs who get this right in 2026 use marketplaces for bounded contractor work and pods for roadmap velocity. The CTOs who get it wrong run six-month Toptal engagements expecting roadmap compression and end up at month seven with a board that has stopped trusting them.

What the numbers looked like, side by side

Lever	Toptal months 1–6	Devlyn months 7–9
Engagement model	Three parallel contractor matches	One pod retainer
Monthly burn (peak)	$42,000 (3 contractors at $14K each)	$9,800 (pod with PM + DevOps shared)
Mid-engagement churn	11 calendar weeks lost over 6 months	0 weeks (internal practice replacement)
Velocity vs historical	Linear (3× engineer count)	4× compounding (AI-augmented workflow)
Roadmap completion at 6 months in	38% against 50% target	Caught up by month 9
Replacement ramp	2–3 weeks per match	24 hours via internal practice

The line that mattered most to him in retrospect was the third: 11 weeks of velocity loss to marketplace churn was the structural cost he had not priced in when he renewed Toptal at month three. Devlyn’s pod-level continuity protected him from repeating that mistake in months seven through nine.

What he tells other CTOs now

I asked the CTO what he tells his peers when they ask. His answer was short.

“If you have a one-engineer gap and your roadmap can absorb a linear addition, post on Toptal — they will deliver. If you have a roadmap-shaped gap and the board is asking for compounding velocity, post a Devlyn discovery call instead. The line is whether the work is contractor-shaped or pod-shaped. Six months of marketplace churn taught me the difference. The board grace period for that lesson is shorter in 2026 than it was in 2023.”

He is not anti-Toptal. He uses Toptal twice a year for bounded one-off contractor work — a six-week migration assist, a niche stack he does not want to staff permanently. The framing is roadmap-mode versus task-mode. The two vendors are not mutually exclusive when the work is genuinely different shape.

What to do if you are at month three or four with Toptal

If you are reading this from inside a Toptal engagement that started clean and is now flattening — the pattern is not your fault. It is structural. The diagnostic questions are:

1. Is the work contractor-shaped or pod-shaped? Contractor-shaped means one role on an existing team that does not need architectural ownership. Pod-shaped means architecture, security, DevOps, QA, and the roadmap as a coherent owned unit.
2. Is the constraint headcount or velocity? Marketplaces add headcount. Pods compound velocity.
3. Has the board started asking why velocity is not multiplying? The answer they want is usually a workflow change, not more headcount.
4. What does the roadmap math need — linear addition or compounding velocity? If the answer is compounding, the marketplace is structurally the wrong instrument.

The cheapest move from month four is parallel evaluation. Keep the Toptal engagement running. Open a 30-minute Devlyn discovery call. Run a 3-day free trial against a real scoped task. Decide based on output, not on rate cards.

The CTOs who run this parallel test in 2026 are converging on the same conclusion: Toptal is correct for bounded contractor work, AI-augmented pods are correct for roadmap velocity. The two are not competing; they are different tools for different shapes of work.

If you are running a $5M–$500M IT organisation and your engineering capacity is the constraint — and the marketplace engagement is starting to feel like it is not compounding — the gap is structural. Book a 30-minute Devlyn discovery call → — no contracts, no commitment. For retainer-grade engagements, the Standing Invitation is where briefs get sent.