#Technical Sales

Articles about Technical Sales — exploring patterns, best practices, and real-world implementations in production systems.

6 posts tagged with technical sales. ← All posts

#A/B Testing (3)#A2A (14)#ADK (8)#AG-UI (6)#AI (9)#AI Agents (335)#AI Architecture (22)#AI Cost (10)#AI Cost Optimization (8)#AI Engineering (291)#AI Evaluation (9)#AI Financial Engineering (14)#AI Gateway (8)#AI Governance (40)#AI Red Teaming (9)#AI Research (9)#AI Safety (12)#AI Security (29)#AI in Production (12)#AML (3)#API Design (10)#API Security (8)#APIs (59)#AWS (17)#Accountability (8)#Accounting (9)#Agent Skills (11)#Agentic AI (25)#Agentic Commerce (12)#Agentic RAG (8)#Agents (4)#Amazon Bedrock (8)#Analytics (3)#Architecture (42)#Attention (3)#Audit (4)#Authentication (11)#Authorization (3)#Automation (11)#Azure (11)#Azure AI Foundry (9)#Backend Engineering (310)#Benchmarks (3)#Best Practices (4)#BigQuery (6)#Business Finance (8)#Business Strategy (55)#C (8)#CI/CD (16)#Caching (11)#Capital Markets (14)#Card Payments (12)#Cards (13)#Career (29)#Causal Inference (8)#Cellular Automata (8)#Checkpointing (4)#Claude Code (8)#Cloud (5)#Cloud Architecture (3)#Cloud Native (10)#Code Review (9)#Coding Agents (8)#Collaboration (6)#Communication (9)#Complexity (8)#Compliance (54)#Computer Networking (9)#Computer Science (40)#Computer Vision (15)#Computer-Use Agents (8)#Concurrency (40)#Consulting (17)#Containers (10)#Context Engineering (14)#Conversational AI (8)#Cost Optimisation (5)#Cost Optimization (3)#Credit (16)#Credit Risk (16)#CrewAI (8)#Crypto (12)#Cryptocurrency (12)#Cryptography (9)#Custody (9)#DSPy (8)#Data (14)#Data Engineering (24)#Data Science (8)#Data Structures (10)#Databases (41)#Deep Learning (20)#Deployment (5)#Design (3)#Design Patterns (10)#DevOps (24)#DevSecOps (22)#Developer Experience (5)#Developer Tools (5)#Differential Privacy (3)#Discovery (4)#Distributed Systems (100)#Documentation (3)#Edge AI (8)#Embeddings (21)#Emotional Intelligence (8)#Energy (8)#Engineering (14)#Engineering Culture (3)#Engineering Judgment (7)#Engineering Practices (16)#Error Handling (4)#Evaluation (69)#Event-Driven Architecture (8)#Explainable AI (8)#FREE-AI (8)#FX (5)#Feature Engineering (3)#Feedback (4)#FinOps (23)#FinTech (6)#Financial AI (14)#Financial Engineering (8)#Financial Systems (129)#Fine-Tuning (12)#Fintech (131)#Flutter (8)#Forecasting (10)#Foreign Exchange (5)#Forward Deployed Engineer (35)#Forward Deployed Engineering (8)#Fraud (10)#Function Tools (5)#Functional Programming (3)#Fundamentals (23)#Fundraising (8)#GCP (5)#GPU (8)#GUI Automation (8)#Gemma (4)#Generative AI (3)#Git (8)#Go (220)#Go-to-Market (31)#Google ADK (36)#Governance (61)#Granite (6)#Graph Neural Networks (8)#GraphQL (3)#Growth (3)#Guardrails (35)#HIPAA (3)#HTTP (3)#Harness Engineering (8)#Hiring (8)#Hugging Face (8)#Human-in-the-Loop (9)#IBM watsonx (8)#Identity (11)#Inference (8)#Information Retrieval (8)#Integration (3)#Intellectual Property (8)#Interfaces (3)#Interpretability (8)#JavaScript (8)#KYC (11)#KYC and AML (12)#Kafka (11)#Knowledge Graphs (10)#Kubernetes (17)#LLM (5)#LLM Inference (8)#LLM Infrastructure (8)#LLM-as-Judge (3)#LLMOps (8)#LLMs (192)#LangChain (8)#LangGraph (11)#Leadership (31)#Ledger (12)#Legal (8)#Lending (14)#Linux (9)#LlamaIndex (8)#Load Balancing (3)#MCP (22)#MLOps (36)#Machine Learning (109)#Marketing (16)#Markets (4)#Mathematical Finance (8)#Memory (15)#Memory Management (5)#Metrics (7)#Microservices (3)#Microsoft Agent Framework (150)#Middleware (6)#Migration (9)#Mixture of Experts (5)#Model Risk (3)#Monitoring (5)#Multi-Agent (10)#Multi-Agent AI (14)#Multi-Agent Systems (73)#Multimodal (3)#Multimodal AI (11)#NIM (5)#NVIDIA (8)#Networking (3)#OAuth (3)#OWASP (7)#Observability (50)#On-Device AI (8)#Ontology (8)#Open Source (7)#OpenTelemetry (5)#Operating Systems (9)#Operations (13)#Opinion (6)#Orchestration (10)#Organizational Design (8)#Payment Rails (16)#Payments (54)#People (8)#Performance (56)#Personalization (9)#Platform Engineering (9)#Policy as Code (3)#PreSales (8)#Pricing (3)#Privacy (13)#Privacy Engineering (3)#Process (4)#Product (30)#Product Management (8)#Production (22)#Programming (10)#Programming Languages (48)#Prompt Engineering (80)#Prompt Injection (15)#Protocol Buffers (3)#Protocols (9)#Providers (4)#Pydantic AI (8)#Python (142)#Quality (3)#Quantitative Finance (22)#RAG (70)#RBI (3)#REST (5)#Rails (16)#Real-Time (8)#Reasoning Models (8)#Recommender Systems (8)#Reconciliation (3)#RegTech (8)#Regulation (10)#Reinforcement Learning (9)#Reliability (56)#Resilience (4)#Responsible AI (5)#Retrieval (3)#Risk (14)#Risk Management (11)#Rust (32)#SLSA (3)#SRE (23)#Sales (9)#Sales Engineering (8)#Scalability (6)#Search (10)#Security (102)#Security Engineering (8)#Self-Evolving Agents (16)#Semantic Web (8)#Sessions (3)#Settlement (9)#Soft Skills (8)#Software (3)#Software Architecture (36)#Software Delivery (9)#Software Engineering (152)#Spanner (4)#Speech (8)#Startups (30)#Statistics (8)#Strands (8)#Strategy (6)#Stream Processing (8)#Streaming (36)#Structured Output (4)#Supply Chain Security (9)#Sustainability (9)#System Design (32)#Systems Programming (56)#Technical Sales (6)#Testing (66)#Threat Modeling (3)#Time Series (9)#Tool Use (23)#Tooling (5)#Tools (4)#Trading (8)#Treasury (6)#Trust (4)#Type System (3)#Type Systems (11)#TypeScript (8)#Validation (3)#Valuation (3)#Vector Databases (22)#Vector Search (11)#Venture Capital (8)#Version Control (9)#Voice AI (9)#Web Development (6)#Workflow (4)#Workflows (14)#eBPF (8)#gRPC (13)#smolagents (8)
Pratik Dhanave · ·4 min read

From Sales Engineer to Forward Deployed Engineer

The AI era is quietly rewriting the technical-sales role. When a demo no longer proves value and the deal is decided in production, the person who wins it isn't the one who presents best — it's the one who can build the win next to the customer. This closing post is about that shift: from sales engineer to forward deployed engineer, the apex role of AI-era technical GTM.

When a demo no longer proves value and the deal is decided in production, the person who wins it is the one who can build the win next to the customer. The technical-GTM spectrum (SE → FDE → CS), why AI made the forward deployed engineer mandatory, the craft tension of scoping and productizing, and how the role becomes a career and a business.

#Technical Sales#Forward Deployed Engineer#AI Engineering#Go-to-Market#Sales Engineering
Pratik Dhanave · ·4 min read

The Technical Win — Proving Value on Real Data

The technical win is the moment an AI deal becomes real: not "the buyer is impressed" but "the buyer has seen, on their own data, against a bar they agreed to, that the thing they feared is handled." This post is about earning that win — turning a scoped proof into undeniable, documented evidence that closes.

The technical win is when an AI deal becomes real: documented evidence, on the customer’s data, against an agreed bar, that the feared risk is retired. The four properties of a real AI technical win, proving value (not model accuracy), the double duty of evaluation and guardrails, and how to make the win undeniable and hand it to the people who weren’t in the room.

#Technical Sales#Evaluation#AI Engineering#Go-to-Market#Sales Engineering#Guardrails
Pratik Dhanave · ·4 min read

The POC Is Where AI Deals Die

The proof-of-concept used to be a formality near the finish line. For AI, it's the crux of the whole deal — and the single most common place AI deals quietly die. Not because the technology failed, but because nobody agreed, up front, what "it worked" would mean. This post is about running an AI POC that converts.

For AI the POC is the crux of the deal — and the most common place AI deals die, almost always from ambiguity, not technical failure. Why AI POCs die, and how to scope one before running it: agree the task, the bar, the data, and the day-after in writing, so the trial becomes a decision procedure that closes.

#Technical Sales#Proof of Concept#AI Engineering#Go-to-Market#Sales Engineering
Pratik Dhanave · ·4 min read

Why a Great AI Demo Doesn't Close

An AI demo is the easiest impressive thing to build and the most dangerous thing to trust. It wows the room, everyone nods, and then the deal stalls — because a demo answers "is this impressive?" when the buyer was asking "will this be dependable on my data?" This post is about the demo trap, and how to make the demo set up the win instead of standing in for it.

A polished AI demo proves your product can do something impressive once, on data you chose; the buyer needs to know it works reliably on data they didn’t. The demo trap, why AI makes it worse, and how to reframe the demo so it earns a scoped proof on real data instead of standing in for it.

#Technical Sales#AI Demos#Sales Engineering#Go-to-Market
Pratik Dhanave · ·4 min read

AI Discovery — Selling Into Fear

Classic discovery hunts for a business pain worth solving. AI discovery has to do that and one more thing: surface the fear. Every serious AI buyer is quietly managing dread about hallucination, cost, security, and lock-in — and if your discovery doesn't find and name those fears, your demo will walk straight into them. This post is about discovery for AI products.

Classic discovery finds a business pain; AI discovery must also surface the fear — hallucination, cost, security, lock-in. The two jobs of AI discovery, the four fears to name out loud, why the best discovery disqualifies, and how to quantify value in the buyer’s terms.

#Technical Sales#Discovery#AI Engineering#Go-to-Market#Sales Engineering
Pratik Dhanave · ·4 min read

Why Selling AI Is Different

The classic technical-sales playbook was written for software that does what the datasheet says. AI isn't that. It's probabilistic, it fails in unfamiliar ways, and a dazzling demo proves almost nothing about whether it will work on the customer's real data. Selling and winning AI deals takes a different motion — this series is about that motion, and this post is why the old one isn't enough.

The classic technical-sales playbook was written for deterministic software; AI is probabilistic, fails in unfamiliar ways, and a demo proves almost nothing about production. Why selling AI is different — probabilistic behavior, invisible difficulty, a fearful buyer — and why the sale’s center of gravity shifts from the demo to production.

#Technical Sales#Sales Engineering#AI Engineering#Go-to-Market

All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.