Start small before you sign a five-year, multi-agent deal | Anatolii Iakimets, Director of Product Marketing, Kibo | Ep. 8

Every pitch for agentic commerce opens with the model. Which frontier lab it runs on, how smart it is, how many PhDs sit behind it. This episode argues the model is the part that matters least.ㅤHosts Matt Johnson and Floyd Blaikie of Pivotree's Data vs. Commerce sit down with Anatolii Iakimets, Director of Product Marketing at Kibo. Anatolii takes the data side: an agent is a model plus a harness, the model is becoming a commodity, and the real work sits in the data and integration layer underneath.ㅤThe friction is clean. Floyd keeps reframing agentic commerce as a familiar platform decision, agents in a trench coat. Anatolii keeps pulling it back to the data. Commerce is deterministic. The price and the tax and the T-shirt size have to be exact, and an agent is only as good as the structured data it can reach and read.ㅤ👤 Guest BioAnatolii Iakimets is Director of Product Marketing at Kibo Commerce, where he focuses on B2C commerce. He has spent more than a decade in commerce and telecommunications, with earlier roles at Bold Commerce, Elastic Path, and Netcracker, and he has worked hands-on with AI and machine learning since around 2015. On this episode he takes the data side, arguing that agentic commerce succeeds or fails on data quality and integration, not on the model you pick.ㅤ📌 What We CoverThe two parts of any agent: the LLM and the harness, the code that tells the model what to doWhy the model is becoming a commodity, and why the switching cost for users stays lowWhy coding and text agents tolerate a slightly different answer every time, and commerce does notWhy the price, the tax, and the T-shirt size have to be accurate to the point, not "good enough"Why an agent has to be integrated like an application, talking to your systems through MCP or an APIHow burning tokens turns into a real budget problem, with Uber's four-month AI burn as the warningThe three things to weigh before you buy: composability, simplicity, and the ability to start smallWhy the "explain" function is the one customers reach for first, and the risk of a three or five year lock-in ㅤ🔗 Resources MentionedKibo (the guest's company)Anthropic (Claude) and OpenAI (ChatGPT) as frontier model providersGoogle as a frontier labDeepSeek and Kimi K2 as open-weight modelsModel Context Protocol (MCP), APIs, and agent-to-agent protocolsMicrosoft Copilot's shift from subscription tiers toward usage-based pricingUber's AI budget storySam Altman on models becoming "intelligence on a tap"