Paid resources for developers

One to one coaching with a co-founder of DesignGurus.io and the creator of the Grokking series, now at Amazon after building and scaling distributed systems and data storage infrastructure at Meta, Microsoft and Hulu. Covers system design, data structures and algorithms, interview strategy and career direction.

Coding and system design coaching with a co-founder of DesignGurus.io, now at Amazon, who was a Senior Development Lead on Azure Storage at Microsoft and a Software Engineer Lead at Meta. Strongest on distributed systems, scalable architecture and interview strategy.

A roster of coaches working at Meta, Microsoft, Amazon, Snap and Cloudflare, bookable for coding, system design or general career coaching. Pick the coach whose background matches the loop you are facing.

Live mock interviews with senior engineers, covering coding, system design or a target company format, each ending in a structured debrief. Rehearsal under real conditions is the part of preparation people skip.

How compensation is actually decided, what is negotiable beyond base salary, and the specific words to use when an offer arrives. A few hours here routinely returns more than a year of side projects.

A sequenced path through the engineering management loop, covering people scenarios, project execution, technical depth and the coding round that many managers are still asked to pass. A very different loop from an engineering one.

The management interview in detail: people scenarios, hiring, performance conversations, project execution and stakeholder work, with the structures that keep an answer from wandering. Manager answers fail on structure more often than on substance.

Aimed above the first management rung, at directors and senior leaders, covering organisational design, strategy, cross functional influence and the scope questions that separate levels. The questions change shape at this level rather than getting harder.

A working engineer's grounding in modern AI: what a model actually does, how transformers and embeddings work, what training and fine tuning involve, and where the current limits are. Written for people who need to build with this technology rather than publish papers about it.

System design for AI backed products, covering retrieval pipelines, vector stores, model serving, evaluation, cost control and the latency budget that makes or breaks the user experience. This round is now appearing in loops that had no AI content two years ago.

Using AI tools deliberately across a job search: sharpening a resume against a specific posting, preparing for interviews, researching companies and drafting outreach that does not read as generated. Practical, and unusually concrete about where the tools help and where they hurt you.

Practice interviews with an AI interviewer that asks follow up questions and gives structured feedback, available whenever you are free rather than whenever a human is. Cheaper and more repeatable than human mocks, and a sensible first stage before you book one.

The course that made system design interviews learnable, working through designs for services like a URL shortener, a news feed, a messaging system and a video platform, each with the requirement gathering, capacity estimates and trade off discussion an interviewer expects.

The full path through system design preparation, from the building blocks up through advanced designs and practice. Follow it in order instead of assembling a curriculum from scattered blog posts.

The building blocks every design answer is assembled from: load balancers, caches, databases, replication, sharding, message queues, consistency models and the CAP trade off. Start here if the full design walkthroughs feel like they assume knowledge you do not have.

The follow on course, working through the real distributed systems that the standard designs are built from, including consensus, distributed storage and coordination. This is the material that separates a senior answer from a mid level one.

The recurring distributed systems patterns behind most designs, including write ahead logs, leases, heartbeats, quorums, segmented logs and consistent hashing. Learn the patterns once and you stop reinventing an answer for every question.

Service decomposition, inter service communication, data ownership and the failure modes that appear the moment a system stops being one process. Interviewers ask about the trade offs, not the diagram.

The named patterns that make service architectures survivable, including API gateway, circuit breaker, bulkhead, sidecar, saga, CQRS and event sourcing. Each one exists because someone lost a weekend to the problem it solves.

How systems actually scale, covering horizontal growth, statelessness, caching layers, database partitioning and the bottlenecks that appear at each order of magnitude. Focused on the reasoning an interviewer is listening for.

A compressed run through the system design round for when the interview is next week and the full course is not going to happen. Enough structure to stop you improvising.

REST, GraphQL, gRPC and event driven interfaces compared on the criteria that actually decide between them: coupling, versioning, latency and who pays the cost of a change. API design rounds are increasingly common and rarely prepared for.

Schema design, normalisation, indexing and the modelling decisions that determine whether a system is pleasant or painful three years in. The data model outlives every other decision in a codebase.

How databases actually work underneath: storage engines, indexes, transactions, isolation levels and the relational versus non relational choice. The layer that makes system design answers defensible instead of hand waved.