# Message test — https://decode.agency/ After reading your page, 13 of 15 personas could name a reason to pick you over a similar option — and differentiation was the weakest of the four. - **Page tested:** https://decode.agency/ - **Audience tested against:** 1. Growing tech companies, where software is the core product. 100–1,000 employees. SaaS platforms, B2B software, telecom technology providers, cloud infrastructure, technology scale-ups. They have internal engineering teams, talk in terms of roadmap and backlog, and need to ship faster or fill specialist skill gaps without long hiring cycles. 2. Established mid-market businesses, where software supports operations and growth but isn't the core product. 50–1,000 employees. Manufacturing, logistics and transportation, healthcare, energy, retail, financial services, hospitality, fintech, Internet of Things. They're modernizing legacy systems, automating manual workflows, or building scalable digital platforms to support new revenue lines. - **Personas:** 15 simulated - **Report:** https://grader.wynter.com/r/full-service-software-development-company-deco-vCPfmiA > These answers are generated by AI, scored on Wynter's B2B Message > Layers framework using behaviorally-diverse simulated personas. The > methodology is real and the critique is directional. What a simulated > persona cannot have is a live budget, a renewal coming up, or a boss > asking about this quarter. --- ## 01 · The scores Every persona answered all four questions. These are four independent proportions of the same panel, not stages of a funnel. | Layer | Question | Cleared the bar | Strength | Of those who passed | | --- | --- | --- | --- | --- | | 1. Clarity | Do they understand what you do? | 15/15 | 84% | 7 without hesitation, 7 with reservations | | 2. Relevance | Can they tell what it solves, and who it's for? | 15/15 | 94% | 11 without hesitation, 4 with reservations | | 3. Value | Do they actually want it? | 14/15 | 74% | all with reservations | | 4. Differentiation | Is there a reason to pick you over the alternatives? | 13/15 | 70% | all with reservations | **Brand alignment** (a side metric, not one of the four layers) — 15/15, 78% strength (all with reservations). Does the page read like the company you actually are? **Fix first: Differentiation.** Earliest failing layer, walking the sequence in order — not simply the lowest score. --- ## 02 · What to change, layer by layer Ordered worst-first. Specific edits, not a restatement of the score. ### Differentiation **Move "1 Project — 1 Team" to the top of "What makes us different".** The one-team-one-project policy is the claim buyers remember, yet it sits second behind "Product-minded". Lead the differentiator block with it and state the consequence for delivery dates. *effort low · impact medium · tested against Give a reason to choose you* **Replace "Agentic engineering" heading with plain wording for what the AI workflows do.** "Agentic engineering" and "product-minded" are undefined internal terms a first-time reader must decode, and any services firm could claim both. Say what the AI workflows replace and how much faster delivery gets. *effort low · impact medium · tested against Plain language* ### Value **Add the savings calculation basis under the railroad case study's $100M figure.** The $100M savings number sits alone with no indication of what was measured or over how long. Add a line naming the baseline, the timeframe, and what was counted. *effort medium · impact high · tested against Proof next to the claim* **Add engagement terms under "Clients who love working with us": team size, ramp time, exit.** A buyer reading "Team extension" or "Dedicated team" cannot tell how many engineers, how fast they start, or how to end the contract. State typical team size, start-to-productive time, and notice period. *effort medium · impact high · tested against Answer the live objection* **Add a regulated-industry proof point under the Fintech and Healthcare expertise cards.** The Healthcare and Fintech cards promise crystal-clear communication and staying "on the money" but show no delivered work in either. Replace the copy with one named project and outcome per regulated industry. *effort medium · impact medium · tested against Proof next to the claim* --- ## 03 · What is working ### The opening segments buyers and names their problems without requiring inference Nine respondents singled out the hero subhead's three buyer segments and matching problem statements as explicit and immediately legible, mapping to legacy modernization and in-house team augmentation. Several noted no hunting or inference was required. > the subhead spells it out plain: "If you need custom AI software, want to fill critical gaps in your engineering team, or wish to modernize your legacy systems, you're in the right place." That's three clear buyer segments in one sentence > > — VP of Product, Cloud infrastructure, 201-500 > tells you the problem and the reader in one line, no digging required. Then the "Tech teams looking for expert engineers" and "Established businesses looking to modernize" sections spell out the two buyer types explicitly > > — Director of Product, Manufacturing, 501-1000 > It was obvious fast, right in the subhead: "If you need custom AI software, want to fill critical gaps in your engineering team, or wish to modernize your legacy systems, you're in the right place." > > — VP of Engineering, Healthcare, 201-500 > the subhead spells it out: "If you need custom AI software, want to fill critical gaps in your engineering team, or wish to modernize your legacy systems, you're in the right place." That's three reader types named in one sentence, so I didn't have to hunt. > > — Engineering Manager, SaaS and B2B software, 51-200 > And the reader is explicitly segmented a few scrolls down: "Tech teams looking for expert engineers" (missing expertise, delivery under pressure) versus "Established businesses looking to modernize" (outdated systems, manual processes). So both the problem and the audience are named, not inferred > > — VP of Product, Cloud infrastructure, 201-500 > the "Tech teams looking for expert engineers" section spells it out almost immediately: "Your team is under pressure to deliver, but you're missing key expertise in a few areas. You need senior engineers who can fill critical gaps and keep delivery on track." > > — Director of Product, Manufacturing, 501-1000 ### Eliminating the hiring cycle for specialist roles was the value that landed One respondent named the removal of hiring-cycle delays for specialist roles as the clear value proposition. > the practical change is I stop losing quarters to hiring cycles for specialist roles I can't fill fast enough internally — I get a "1 Project — 1 Team" senior team parachuted in, like the Metaswitch case where they scaled a small iOS team to 21 engineers across four platforms. > > — Director of Product, Manufacturing, 501-1000 ### The one-team-per-project policy is the differentiator respondents could repeat back Four respondents named the one-project-per-team policy unprompted as a concrete, verifiable differentiator against competitors. It was the most consistently cited distinguishing claim on the page. > The "1 Project — 1 Team" policy with the explicit line "We take on fewer clients than we could" is the one thing that could tip a real decision — it's a concrete operating commitment, not a slogan > > — VP of Product, Cloud infrastructure, 201-500 > The "1 Project — 1 Team" policy plus the line "we take on fewer clients than we could" would actually tip me toward them over a competitor, because it's a concrete operating claim — not just "we care" — that I could verify with a reference > > — Director of Product, Manufacturing, 501-1000 > The "one team, one project" policy is the specific differentiator — most staff-aug shops let engineers rotate across clients, and DECODE explicitly says "We take on fewer clients than we could" to avoid that, which is a real business tradeoff they're claiming to make, not just a slogan. > > — VP of Product, Cloud infrastructure, 201-500 --- ## 04 · What the personas said ### Service breadth and undefined buzzwords obscure what the business actually is Three respondents said 'agentic engineering' and 'product-minded' go unexplained, and that spanning AI, legacy modernization, MVP and DevOps hides the primary business model. One said the hero presents three problems where one would land. > none of them are defined anywhere on the page, so I can't tell if "agentic" means they use AI copilots internally, sell agent-building as a deliverable, or it's just a 2024 buzzword slapped on standard staff-aug. > > — CTO, Logistics and transportation, 51-200 > the sheer breadth — "AI software development," "AI agent development," "legacy modernization," "MVP development," "DevOps" all sitting in one services grid made me hunt for the actual core business model underneath the labels > > — Director of Product, Manufacturing, 501-1000 ### The proof stops short of the commercial details needed to advance a deal Eight respondents said the case studies omit day rates, ramp speed, exit terms, and integration detail, and that the railroad study's $100M savings figure has no visible calculation. Three said they would need named client reference calls before proceeding. > the case studies (railroad platform handling 400K+ reservations, the Royal Caribbean crew app) are the only things that make me believe it, and they're about other companies' outcomes, not proof of how fast they'd ramp on my stack or what it costs to unwind if it doesn't click. > > — VP of Product, Cloud infrastructure, 201-500 > I'd want the Norfolk Southern and Royal Caribbean people on a reference call before I'd move past a first conversation — named logos on a page aren't proof, a 20-minute call with someone who lived through onboarding them is > > — Director of Product, Manufacturing, 501-1000 > the specifics I'd actually need - day rates, how fast a team ramps, what "fully integrated after strict due diligence" actually meant on the ground, whether the 21-engineer scale-up caused churn or rework - aren't there. > > — Engineering Manager, SaaS and B2B software, 51-200 > A verified reference confirming a dedicated team was staffed and shipping production code within 2-4 weeks of kickoff, with velocity that held (or improved) by month three - not just DECODE's own case study numbers. > > — VP of Product, Cloud infrastructure, 201-500 ### Respondents in regulated sectors found no case study for their industry Three respondents noted the absence of healthcare and financial services or regulated-industry proof, seeing only generic enterprise case studies in its place. One also flagged a missing manufacturing persona despite manufacturing being listed as expertise. > "manufacturing" is in their fields-of-expertise list but gets one soft paragraph, not a persona block like the "tech teams" one > > — Director of Product, Manufacturing, 501-1000 ### Absent pricing and unverifiable stats undercut the enterprise posture Two respondents said missing pricing, missing team-size detail, and unverifiable collaboration statistics reduce trust. One felt the messaging aims at a generic mid-market buyer rather than their specialist infrastructure context. > no pricing, no named team sizes/HQ location beyond "EU-based," and stats like "4.5 years of client collaboration, on average" with no source — so it reads credible but I'd still want a reference call before believing the polish matches reality. > > — Engineering Manager, SaaS and B2B software, 51-200 > it feels like it was written for "any mid-market engineering leader," not for my situation. > > — VP of Product, Cloud infrastructure, 201-500 ### Readers correctly identify the model as custom contract engineering, not a product Four respondents landed on the same read: an outsourced custom engineering services firm offering team extension, dedicated teams, or end-to-end builds, not a licensed product or SaaS. One characterized the core as staff augmentation rather than AI. > They're a custom software development shop - basically an outsourced engineering firm that plugs senior teams into your projects > > — VP of Engineering, Healthcare, 201-500 > It reads like a dev shop/consultancy, not something I'd "purchase" in the traditional sense — it's a staffing and delivery decision > > — Director of Engineering, Financial services, 501-1000 > They're a custom software dev shop / consultancy - basically outsourced engineers you hire to build or modernize your product > > — Engineering Manager, SaaS and B2B software, 51-200 > Team extension, Dedicated team, Build-Operate-Transfer" is the real offer; the AI and "agentic engineering" language is positioning, not the core business. > > — VP of Engineering, Healthcare, 201-500 --- ## 05 · The hardest read An adversarial pass over the findings. Every claim below was checked against the panel's own answers; unsupported ones were dropped. - **The page gets read as staff augmentation, collapsing the AI positioning it leads with** *(high)* Four respondents independently described the model as outsourced custom contract engineering, one calling the core staff augmentation rather than AI, while three said 'agentic engineering' and 'product-minded' went unexplained. The premium framing does not… - **Strong segmentation at the top buys nothing because the page cannot carry a deal past first interest** *(high)* Nine respondents found the hero's buyer segments and problem statements immediately legible, but eight said case studies omit day rates, ramp speed, exit terms and integration detail, and three demanded reference calls before proceeding. - **Unsupported numbers actively subtract trust rather than merely failing to add it** *(high)* Eight respondents flagged the railroad study's $100M savings as having no visible calculation, and two cited unverifiable collaboration statistics plus missing pricing and team-size detail as reducing trust. - **Listing regulated and manufacturing expertise without matching proof reads as an overclaim** *(high)* Three respondents found no healthcare, financial services or regulated-industry case study and saw generic enterprise proof instead; one flagged a missing manufacturing persona despite manufacturing being named as expertise. - **Breadth of services is priced in credibility, not read as capability** *(medium)* Three respondents said spanning AI, legacy modernization, MVP and DevOps hides the primary business model, and one said the hero stacks three problems where one would land. Two more read the messaging as aimed at a generic mid-market buyer. - **The only repeatable differentiator is an operational policy, not technical capability** *(medium)* Four respondents named one-team-per-project unprompted as the most consistently cited distinguishing claim, while the AI and agentic language went unexplained for three others. The page wins on process discipline, not expertise. --- ## 06 · Who answered | # | Role | Industry | Company size | | --- | --- | --- | --- | | 1 | VP of Product | Cloud infrastructure | 201-500 | | 2 | Director of Product | Manufacturing | 501-1000 | | 3 | CTO | Logistics and transportation | 51-200 | | 4 | VP of Engineering | Healthcare | 201-500 | | 5 | Director of Engineering | Financial services | 501-1000 | | 6 | Engineering Manager | SaaS and B2B software | 51-200 | | 7 | VP of Product | Cloud infrastructure | 201-500 | | 8 | Director of Product | Manufacturing | 501-1000 | | 9 | CTO | Logistics and transportation | 51-200 | | 10 | VP of Engineering | Healthcare | 201-500 | | 11 | Director of Engineering | Financial services | 501-1000 | | 12 | Engineering Manager | SaaS and B2B software | 51-200 | | 13 | VP of Product | Cloud infrastructure | 201-500 | | 14 | Director of Product | Manufacturing | 501-1000 | | 15 | CTO | Logistics and transportation | 51-200 | --- ## 07 · Before you act on this The methodology is real, and the critique is directional. What a simulated persona cannot have is a live budget, a renewal coming up, or a boss asking about this quarter. **Validate anything you're betting on with real ICPs who are actually in-market.** Being wrong is more expensive than you think. Finding out is cheaper than you'd guess. Wynter runs message testing with verified B2B professionals — trusted by HubSpot, RingCentral, Shopify, Cognism, Paddle, Veeam, Rippling and Miro. This report is kept for 60 days from 2026-09-17, then deleted along with the personas and their answers.