Lakshya

Learn

26 books, 341 chapters

Written to teach, not to summarise. Every chapter carries diagrams built to show a mechanism rather than decorate a page.

13 CHAPTERS The Interview Spine The seven things every archetype on this site tests, whatever the job title. Start here if you are preparing for an interview. Cross-cutting. Each chapter is linked from every role that tests it. 31 CHAPTERS Software Engineering What postings now ask for, system design at the level actually assessed, product sense for engineers, code and review, debugging and the coding round, what changes from mid to staff, the loop round by round, and choosing a track. The largest field in this atlas at 2,609 postings. Written for the general software engineering loop rather than any one specialism. 20 CHAPTERS LLM Systems Engineering Seven chapters on the engineering underneath applied AI: the roofline and KV-cache arithmetic that explain every serving decision, quantisation with the evidence, serving stacks and the prompt-cache traps that cost real money, retrieval internals and whether long context replaced RAG, agents at the token level, evaluation with actual statistics, and what won in post-training. The technical companion to AI from First Principles. Every claim carries its source quality — measured study, vendor documentation, or flagged as unverified. 10 CHAPTERS AI from First Principles Seven chapters, no mathematics assumed. What a model actually is, what training means, why it is confidently wrong, embeddings, RAG, agents, and evaluation. Written for people who have to make decisions about AI without having built it. 18 CHAPTERS Networks, Automation, Connectivity & Data Centres Twelve chapters from a single packet to a submarine cable. Subnetting worked by hand, BGP and why hijacks succeed, DNS and the two outages worth knowing by name, TLS and the expiry that still takes down companies, cloud networking with the arithmetic, transit and peering, colocation and what an AI rack did to the industry, and four debugging scenarios worked end to end. Written for infrastructure, platform, SRE and security candidates. No prior networking assumed — chapter 2 starts at binary. 15 CHAPTERS SDLC, DevOps & Developer Experience How software actually gets from a developer's machine to production: deployment strategies and the version-skew problem underneath them, infrastructure as code and the state file that runs everything, pipeline design that people do not route around, and the software supply chain link by link. Written for platform, DevOps, SRE and developer-experience candidates. Every chapter names the failure mode, not just the practice. 9 CHAPTERS Cloud Platform Engineering Seven chapters comparing the three major clouds where they genuinely differ: the compute spectrum and the ceilings that decide it, managed Kubernetes and the address exhaustion nobody plans for, identity models that do not transfer, networking and the internal traffic that outcosts your egress, storage and database traps, committed-use and spot mechanics, and an honest read on frameworks, market share and certifications. Written for platform, SRE and solutions-architect candidates. Provider names are used sparingly on purpose — the structural differences outlast the branding, and every price should be re-checked before you quote it. 12 CHAPTERS Security Engineering Four chapters on the security work that is not about AI: cryptographic choices with one right answer each, the vulnerability classes that actually cause breaches and their structural fixes, the cloud misconfigurations that appear in nearly every incident report, and detection engineering with the first hour of a response. Written for engineers rather than for a certification. Every fix here addresses the class rather than the instance, and every claim says how you would verify it. 33 CHAPTERS Infrastructure & Reliability Reliability and error budgets, capacity arithmetic, networks, storage and the restore you have not tested, the physical layer, a debugging method that transfers, running production, and an honest look at Kubernetes. Plus a Middleware section — web and application servers, messaging (IBM MQ, Kafka) and managed file transfer, from basics to licensing and cost. For the Platform, IT Infrastructure and SRE archetypes — and for anyone whose interview will involve designing a system with numbers attached. 13 CHAPTERS Securing & Governing AI The attack surface that is genuinely new, the risks that are old in new clothes, model risk, what audit evidence looks like, the frameworks, responsible AI as controls rather than principles, the enterprise AI gateway, measuring harm, and what the law actually requires. Assumes AI from First Principles. Read that one first if any of it is unfamiliar. 16 CHAPTERS Identity & Access Authentication versus authorisation, federation, the joiner-mover-leaver lifecycle, entitlements, privileged access, secrets, and machine identity. Deliberately not framed through AI — this is a discipline in its own right. The last chapter is where the two meet. 13 CHAPTERS Product & Delivery Prioritisation that survives contact, writing that lets engineering start, discovery when your users are not consumers, measurement and its failure modes, dependencies and honest status, saying no well, pricing and unit economics, and scoping a non-deterministic feature. For the Product and Delivery archetypes. Written for B2B, platform and internal contexts, which is what most postings in this atlas actually are. 9 CHAPTERS Engineering Leadership What changes at each level, hiring and holding the bar, growing people and managing someone out, organisational design, running a distributed or GCC organisation, technical strategy, budget and headcount, and what each interview round actually tests. For the Leadership archetypes, including the site and GCC roles — the distributed-organisation chapter is written for the Indian market specifically. 16 CHAPTERS Data Platform & Analytics What the job actually is now, modelling and grain, data contracts and who gets paged, quality that is not a dashboard, streaming, governance, cost, serving the AI workload, Databricks versus Snowflake, and statistics without the degree. For the Data Platform archetypes. Built on 225 postings where compliance outranks SQL and real-time outnumbers batch seven to one. 16 CHAPTERS Databricks & Snowflake From first principles to production: the problem both solve, columnar storage, how Delta and Iceberg turn files into tables, how each engine executes a query, each platform in practice, performance, cost control, governance, and choosing between them. Built because 66% of enterprise data postings name one of these by name and 30% name both. Assumes no prior knowledge of either. 18 CHAPTERS Analytics & BI Tools The four layers of the analytics stack, then Power BI, Tableau, Looker and Alteryx each in practice — what they are genuinely good at, where they hurt, how to choose with real scenarios, the licensing models that bite, and making analytics actually get used. Written to be comparative rather than promotional. The recurring argument is that most tool disputes are really disputes about which layer owns the metric definition. 6 CHAPTERS Technical Go-To-Market Four jobs that look like one, discovery and the demo, proofs of concept that actually end, escalations and the account about to churn, the loop and the presentation round that decides it, and technical support as a route into product companies. 1,426 postings. Customer-facing language in 99%, technical depth in 60% — engineering jobs where the deliverable is a customer's decision. 5 CHAPTERS Sales What sales postings actually ask for, the roles and how they differ, pipeline and forecasting, selling technical and AI products, the loop, and the honest version of crossing over from a technical role. 2,173 postings. Written as evidence rather than coaching — it reports what employers ask for and is explicit about the limits of that. 5 CHAPTERS Product Design & UX What design postings ask for, designing for systems that are sometimes wrong, research at real sample sizes, design systems and accessibility, and the portfolio review that decides the loop. 185 postings — a smaller field here than its visibility suggests, and the one where AI appears most often at 93%. 4 CHAPTERS Legal, Finance & People Business functions inside a technology company: commercial counsel and legal operations, technology finance and SaaS metrics, recruiting and people operations — and why all three are now systems-building jobs. 632 postings. Scaling in 93%, data and analytics in 91% — these functions are asked to build systems, not process transactions. 8 CHAPTERS Trading & Capital Markets Eight chapters on how markets actually work: the order lifecycle end to end, the limit order book and how a price is made, the Indian and US market structures side by side, what each instrument is really for, the full cost of a trade, market data and the errors that ruin research, and the latency budget. Written from exchange, regulator and vendor sources rather than from the job-posting corpus. Parked at eight chapters — risk and margin, surveillance, backtesting and the trading interview are drafted but not yet published. 12 CHAPTERS Technical Analysis Twelve chapters that teach charts the way a researcher would: what each claim actually is, what the evidence supports, and the control you would need to believe it. Structure, levels, moving averages, oscillators, volatility, volume, candlestick patterns, Smart Money Concepts assessed honestly, and a full methodology for testing a rule without fooling yourself. Written to be usable by someone trading their own money and defensible in a quantitative interview. Every claim carries its evidence position, and every chapter names the control. 8 CHAPTERS Security Engineering & Tooling What each category of security tool structurally cannot see, what the evidence actually supports, how the market consolidated, and what the 5,197 postings say the job is. The general security book. Securing & Governing AI is the AI-specific companion — this one is about the discipline as it is practised and bought. 13 CHAPTERS Banking & Capital Markets Systems What Indian banks and financial institutions actually run — core banking, payments, lending, treasury, custody, the registrar duopoly and regulatory reporting — and, just as usefully, which of it can be verified at all. Written from regulator and exchange publications, bank annual reports and dated vendor announcements — not from the job-posting corpus, which contains no banks. Each chapter states which claims are sourced and which are not. 6 CHAPTERS Blockchain, Honestly What a blockchain actually is, how consensus and smart contracts really work, how the money actually gets stolen, and a four-question test for whether it is the right tool — written for someone meeting the subject for the first time. Written from primary sources: protocol documentation, Cambridge's 2025 mining study, RBI and NPCI publications, ASIC's enforcement action against ASX, and post-incident reports. The job-posting corpus behind this site mentions blockchain zero times in 4,556 descriptions — chapter 1 says so plainly, and this book exists because the subject is worth understanding, not because the hiring evidence supports it. 12 CHAPTERS Microsoft 365 & Copilot in the Enterprise How a Microsoft 365 estate is actually built, licensed and governed — tenant, identity, workloads, devices, Purview and Defender, every licence tier with current prices, and then Copilot and Copilot Studio from the request path to the evidence on whether they deliver. The corpus behind this site mentions Microsoft Entra ID in 8.1% of 3,010 job descriptions — a real hiring market — but Microsoft 365 itself in 0.7%, Intune and Purview in about 0.1% each, and Microsoft 365 Copilot and Copilot Studio in none at all. Chapter 1 states that up front. Written from Microsoft Learn, official pricing and licensing pages, dated Microsoft announcements, and independent evaluations — every price observed August 2026 and dated as such. Two claims are flagged in-text as unresolved because live Microsoft pages contradict each other, and one widely-repeated statistic is identified as a citation-chain error rather than repeated.