100 Job Strategies
100 Job Strategies · 56 of 100
Stack Detection
Know their exact setup before you apply. Specificity beats seniority in screening.
In short
Free tools reveal which technologies a company's website and products actually run on, and job postings, engineering blogs and public repositories fill in the rest. Knowing the real stack lets you write an application about their specific environment rather than about generic experience, which is what screening rewards.
The situation
A job posting lists eleven technologies. Candidates dutifully claim experience with all eleven, and every application looks identical.
Meanwhile, a free browser tool reports what the company's product actually runs on. Their engineering blog describes the migration they are halfway through. Their public repositories show the conventions they use. A conference talk from their principal engineer explains why they made a particular architectural choice.
None of that is in the posting.
One candidate writes about the eleven listed technologies. Another writes about the migration and the specific problem it creates.
Why this works
Job postings are written by committee and describe an idealised environment. The real stack — what is actually running, what is being migrated away from, what causes pain — is different, more specific, and largely discoverable.
Screening rewards specificity heavily. A screener comparing applications cannot distinguish between candidates claiming the same generic experience, but a candidate who references the company's actual architecture is immediately distinguishable, because that knowledge cannot be faked in a template.
The information is genuinely available. Technology profiling tools report what a website runs on. Engineering blogs describe real decisions in detail. Public repositories reveal conventions, tooling and code standards. Conference talks by staff explain architecture. Job postings across several roles, read together, map the organisation's technical landscape.
It also improves your judgement about whether to apply. A stack you enjoy working in, or one being migrated towards something you know, is a much better fit signal than a title. Discovering the environment after joining is how people end up unhappy.
In interviews the same knowledge compounds. Being able to ask about a specific architectural decision rather than general questions signals that you think like an engineer who has already started working there.
How to run it
- 1
Profile the public-facing product
Browser extensions and web services identify frameworks, analytics, hosting and infrastructure from a public site. Free and immediate.
- 2
Read their engineering blog properly
Companies write about migrations, incidents and architecture decisions. This is the richest source and almost nobody reads it before applying.
- 3
Look at public repositories
Open-source projects, published libraries and shared tooling reveal conventions, languages and standards that no posting mentions.
- 4
Read several job postings together
One posting shows a role. Five postings across teams map the whole technical estate and show what is being invested in.
- 5
Watch conference talks from their engineers
Staff speaking at conferences describe real systems in detail, including the problems they have not solved.
- 6
Write the application about their environment
Reference the specific migration, the actual architecture, the real constraint. That is what makes you legible among identical applications.
What to say
When it does not work
- Detection tools are only partly accurate. They see the public surface, not internal systems. Treat results as indicative rather than definitive.
- Stacks change constantly. A blog post from two years ago may describe something they have since replaced. Prefer recent sources.
- Overstating familiarity. Referencing their architecture is good; implying deep expertise you lack collapses in a technical interview.
- Being a know-it-all. Explaining their own system back to them, or criticising their choices unprompted, reads badly.
- Backend and internal systems are invisible. Profiling reveals the public surface only. Much of the interesting work is not detectable from outside.
Every other candidate is writing about the eleven technologies in the posting. Almost none of them know what the company is actually running.
Questions
What tools actually reveal a company's technology stack?
Browser extensions and web services that profile a public website can identify frameworks, content management systems, analytics, hosting providers and various infrastructure components at no cost. Beyond automated detection, the richer sources are the company's own engineering blog, its public code repositories, conference talks by its engineers, and several job postings read together. The automated tools are a starting point rather than the substance of the research.
How accurate is automated stack detection?
Reasonably accurate for the public-facing surface and largely blind to everything else. These tools identify what a browser can observe, which covers front-end frameworks, analytics and some infrastructure, but reveals nothing about internal services, data platforms, build systems or the architecture behind the interface. Since much of the interesting engineering work sits precisely in that invisible portion, treat detection results as one input alongside blogs, repositories and postings.
Is it risky to reference their architecture in an application?
It is risky only if you overstate your familiarity. Referencing a migration described on their public blog and connecting it to comparable work you have genuinely done is strong. Implying detailed knowledge of systems you have only read about will collapse in a technical interview, where someone who works on those systems daily will ask a follow-up question. Keep the reference specific but modest, and frame it as something you noticed rather than something you know intimately.
Does this work for non-engineering roles?
The same principle applies with different sources. Marketing candidates can identify a company's analytics, email and advertising tooling from public signals. Sales candidates can often determine the CRM and outreach stack. Operations candidates can infer systems from job postings across the team. The underlying move is the same: research the specific environment rather than writing about generic experience, because specificity is what distinguishes applications during screening.
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