Salesforce End-to-End Implementation Handbook, Kristian Margaryan Jørgensen

Salesforce End-to-End Implementation Handbook, Kristian Margaryan Jørgensen

A long time the <packt> publishing offered all of their books for really good price. I bought them all but didn’t really have time to read them for a long time, but finally I started one by one.

The End-to-End implementation somehow made it on top of the list and I really enjoyed the book. Kristian has really similar approach to implementations and the book resonated very well with me.

14 chapters, each with intro and summary, covering the whole process. Which activities, whom to include, what to take care about. I feel it is almost aimed at the companies implementing internally, to people without Salesforce experience. Some of the steps/tasks/chapters are so obvious, at the same time I feel they can bring a real value to someone at the beginning of their journey.

  • overview of current business capabilities – I always hated this diagram so much yet understand it can bring an immense value. The tricky part for me is, that every single one of us can have a different view on the situation, can group and name the capabilities differently and it was always hard for me to come with something I would be happy with, something which won’t be obvious to everyone since beginning but would bring some new insights – but that’s probably not needed at all;
  • list of delivery methodologies – I still struggle with the subtle differences between Agile, Scrum and Kanban and probably like some bits from each of them. Obviously I won’t be a great project manager;
  • change managements frameworks – important part of every project which is being ignored on every single project I’ve been part of and some simplified into „management will send an email“ (in its best form). Seeing three frameworks listed in the book I want to learn more and while there is this module on Trailhead I don’t feel it gave me enough;
  • KPIs or how we will spot successful implementation – very often I have to wonder how the implementation itself might improve those KPIs -> I do understand lowering processing time, but generate more leads?
  • I’ve never heard of Conway’s law which says that companies do mostly lift and shift into new system, unless provided external input -> strong case (according to Kristian) to involve an implementation partner. Sadly I remember the implementations where the analyst just asked how the processes work now and didn’t care to suggest any possible improvements;
  • a user story should be linked to business objectives, should have a purpose bigger than moving the process into its next step, they shouldn’t describe the solution but rather the need, problem and outcome (YES!). And another book I should prioritize – Salesforce Business Analyst Handbook;

Oftentimes, experienced functional consultants are asked to act as business analysts to run workshops, illicit requirements, and challenge the organization’s assumptions and old way of working. However, solid business analyst skills are distinct from declarative development on the Salesforce platform. While some functional consultants are great business analysts, not all are.

  • deployment plan should include not just the pre/post deployment steps (still can of weird we need them these days when automated pipelines should handle everything) BUT also stakeholder communication plan – back to change management and the whole „project awareness“ topic which is hard to see in the wild. And I spoke with Ceska Sporitelna (in Czech) it is super hard as well as people don’t have really time to grasp any extra communication and are very often surprised later on that some features already exist and they don’t have a clue;
  • speaking about communication, learning and documentation that’s one of the hardest topic I ever faced – as I always acted on the partner side, this was the typical area the customer didn’t want to pay for and rather do it themselves (but never had capacity to do so). Seeing what „training“ might/should include as everyone has different affinity to different learning methods gives me so many ideas, which would make the training the most expensive part of the delivery – workshops, videos, cheat sheets, one-pagers, FAQ, in-app guidance and all of that grouped by different personas and constantly updated. I probably know why at IrishDreamin the ClickLearn application won the demojam;
  • when to transfer from hypercare to ongoing production support? As a partner we push into as soon as possible, seeing these four questions (have you aligned your processes, is the team trained and onboarded, are you reaching adoption targets, are you begin to achieve the business results you laid out) it should take way longer than what we typically aim for. But it is back to the KPIs you want to achieve, some of them are usually pretty long term I would say. And Kristian says kind of the same in the summary of the chapter, speaking about 1 – 12 months to begin achieving the results, not sure we should wait with go-live for that long;

Shield the development team from the Steering Committee meeting

  • the continuous improvement phase after go-live and consideration to modify the partner model – different partner (due to different knowledge/experience), in-house combined with partner (and where is the line), full in-house or anything completely different;
  • how to translate new feature requests into existing capabilities of your implementation and how to handle (limit/promote) the fact that as people start using the platform and learn more about the possibilities (out of the box, configuration, development) they will utilize the platform more;

All in all such a great book to learn how to deliver product into a company (yours or someone else). While there are references to Salesforce I don’t feel it is related only to SF, can be rather used by anyone.

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O Salesforce s developery

V mé sérii povídání o „rolích“ v ekosystému jsem vývojáře nějak odsunul na konec a konečně na ně došlo – povídali jsme společně s Michalem VerneremDavidem Rabiňákem.

Pokud jsem měl na začátku připravenou osnovu a základní otázky, tak to celé šlo z okna hned po úvodním představení – o AI jsem se chtěl možná tak jenom lehce otřít a nakonec jsme nemluvili skoro o ničem jiném. Což jasně ukazuje jak moc se ten svět posunul a jak moc mi asi ujel vlak, když si od AI nechám občas jenom něco poradit, ale neúkoluji ji jako svého kolegu.

Zápisky:

  • Role vývojáře se mění na „orchestrátora agentů“
  • Znalost platformy zůstává klíčová, i když píše agent
  • Výstupy agentů vždy vypadají dobře – i když jsou špatně
  • Paralelní práce s agenty je vyčerpávající
  • Agentovi nelze věřit jako programu
  • Jak chceš vyvíjet, jaké knihovny použiješ, jak bude vypadat dodávka – tohle si musíš vyřešit na začátku projektu. Potom to ovlivňuje úplně všechno.
  • Správa kontextu a tokenů bude klíčová disciplína
  • Juniorní vývojář není mrtvý – záleží na mindsetu
  • Headless Salesforce je boj o přežití, ne nová příležitost
  • Agentforce není mrtvý koncept – ale není pro každého. A někdy je to přesně to co potřebuješ
  • Custom MCP server/end pointy jako cesta ke „snadnému zabezpečení“, protože securita bude klíčová a dost často je ohromným technologickým dluhem
    Listen on Apple Podcasts Listen on Spotify

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    Summary of our User Group about AI and other

    Last month we had another meeting for our user group, and I still have great feelings about it, feel it was one of the best in months even though I don’t know why I feel that. Maybe it was how the speakers have been selected – I took those, who didn’t make the cut for CzechDreamin and somehow their topics mostly complement each other and it makes an interesting mix. Put a lot of people registered and actually attending, being in the new Actum‚s offices and much more, it was such a great event.

    But the real question is what I took away, besides the great chats, being able to speak with HR person who sees the market from outside, meeting bunch (like a lot) of new people I don’t remember seeing before and hearing a great feedback about how welcoming the community is and how even the new joiners weren’t afraid to jump into the debate and ask questions. Wow!

    You can find the recordings (and second part) on Youtube and I shared the presentations on Google Drive.

    Dina McLaughlin – The Platform Has Moved on – Have You? Pivoting in the Age of Agentic AI

    What a great opener for the whole evening. Dina nicely summarized what happened on the market/in the industry, how it changed her life, how it is all quicker. At the same time we are moving from detesministic to probabilistic systems, where we cannot really trust or predict the output. Our roles will be more about orchestrations, reviewing and guiding, the human-in-the-loop critical due to context, creativity and bias awareness.

    AI is already changing day-to-day work – for example junior devs asking AI instead of seniors, which is great and bad at the same time (cannot find the article where I found how crucial it will be to keep the human interaction and experience in the loop as well).

    • The pace of change is no longer linear — it’s exponential and hard to keep up with.
    • Consultants face the hardest shift → need to become transformation advisors, not just implementers.
    • Businesses are confused about AI (what to automate vs what needs AI).
    • Rise of autonomous agents + voice interfaces → interacting with systems without UI.
    • Strong emphasis on continuous upskilling – learning is now lifelong and non-negotiable.
    • Discussion around middle management potentially shrinking (AI replacing coordination roles).

    Michal Verner – The Developer Who Wasn’t There: Autonomous Salesforce Development with Claude Code

    👉 Can an agent take a user story and deliver a full feature (code → tests → UI → PR) autonomously?

    • AI can orchestrate the full pipeline, but only with heavy upfront setup (skills, rules, MD file, tooling) – and I had to laugh here, because it can generate it all but at the same time it expects it from you and you can get it from Reddit or other places, so now we will spend time googling skills and trying the best one just so the AI can generate the things better and quicker at the end (or maybe not)
    • I need to learn new words, to fully understand what it is doing – Unravelling, really?
    Should I learn a new words? Unravelling you say?
    • The cloud.md file is the real “brain”: acts as instruction manual + standards, must be continuously refined, you “earn it” over time through iteration
    • quality is inconsistent – sometimes over-engineered (too many guards, extra code), requires review or additional agents for validation
    • Interesting shift in effort:
      👉 Today: time spent coding
      👉 Future: time spent designing instructions, pipelines, guardrails
    • The agent doesn’t “understand everything” – it searches relevant files on demand, not full context; surprisingly effective even on large codebases
    • Dev behavior shift: “I’m not really writing much code these days” → developers moving toward guiding, nudging, reviewing
    • it was interesting to me that those agents took the whole presentation (almost 30 minutes) to generate and deploy the code, I always have a feeling the „animation“ of how it write the text is just to slow us down and it can generate the whole code base in a blink of eye

    💬 Overall feeling in the room

    • Curiosity → “does this actually work?”
    • Surprise → “okay, it kinda does…”
    • Skepticism → “but is this maintainable / safe?”
    • Humor → jokes about “agent replacing husband” / rubber duck debugging
    • Realization → this is powerful, but not plug-and-play

    Aleš Remta – From 75% Coverage to Sustainable Apex

    • Sustainable Apex = long‑term velocity, not short‑term hacks
    • Good code must be understandable, changeable, reliable, and modular – clear boundaries and contracts reduce cognitive load and prevent ripple‑effect bugs when modifying code
    • Tests are not for coverage – they’re for proving requirements
    • Tests are the best design tool – Writing tests first forces better API design, clearer interfaces, and more modular architecture
    • Writing tests last leads to brittle, implementation‑cementing tests – When tests are written after the code, they often mirror the implementation too closely, making refactoring painful and discouraging change
    • Test‑first exposes requirement gaps early – Writing tests before implementation reveals missing or unclear requirements before code is written, reducing rework and surprises at the end of development
    • Use wrapper objects (e.g., DiscountRequest) to stabilize interfaces – Passing primitives or SObjects directly leads to exploding method signatures. A wrapper object keeps the interface stable even as requirements evolve .
    • Guiding principles: be intentional, strict with API contracts, write more tests, and write them earlier

    Dominik Hlaváč – MCP Servers: Elevating Salesforce Development

    • Why MCP matters: AI needs context, and MCP provides it – compares MCP to a “USB cable for AI” that lets the model see your files, metadata, and org context – something base LLMs cannot do
    • MCP architecture: client ↔ MCP server ↔ tools/resources – The server exposes tools (APIs, local files, custom logic) that the AI can call. The AI “remembers” available tools and uses them to act.
    • Salesforce DX MCP server wraps the CLI into tool groups – It exposes org management, metadata operations, test execution, LWC tooling, and DevOps capabilities
    • Ecosystem is exploding: Figma, GitHub, Atlassian, many more – MCP servers now exist for design, code, documentation, and workflow tools. The official registry is still in preview.
    • Real use cases: dependency mapping, scratch‑org prototyping, impact analysis – MCP can automate org introspection and selective deployments: “List the org and see the whole trajectory of some attribute…”
    • Limitations today: models can be lazy, inefficient, or loop endlessly – who knows how many API tools your „simple“ query will take at the end?
    • Security & pricing concerns: API safer than chat, local models possible, MCP likely to become paid – “Running the API is much safer.”

    And the group discusses future pricing, API consumption, and guardrails. 9pm and people are slowly heading out of the building, 10pm and we finally closing the day. Thank you all!

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    O Salesforce ve Spořce

    Česká spořitelna, banka, kterou v Česku zná asi každý. A v Salesforce komunitě asi každý ví – protože headhunteři už museli každého oslovit alespoň dvakrát – že používají Salesforce. V roce 2023 začali s implementací, o rok později šlo do živa první MVP a od té doby to rolují na další a další věci a Salesforce je tak jedním z hlavních stavebních kamenů jejich systémů.

    Podcast jsme plánovali dlouho, ale nakonec vznikl – jako většina skvělých věcí – v podstatě ze dne na den. Ohromné díky Spořce za jejich interní studio, které se postaralo o skvělou kvalitu zvuku a my jedno brzké ráno věnovali povídání s Martinem VágneremMichalem Řehákem. Čas byl omezený a tak mám pocit, že je to asi jeden z nejrychleji mluvených podcastů co jsem kdy natočil, tak případně si to zpomalte.

    Zápisky

    • Salesforce ve Spořitelně není „jen CRM“, ale celý ekosystém, který propojuje sales, service, marketing, data i interní procesy.
    • CRM v bance neslouží jen k evidenci klienta, ale hlavně k řízení interakcí, přípravě na schůzky a podpoře poradenství.
    • Velké organizace netrpí technologií, ale hlavně procesy, prioritami a stakeholder managementem.
    • Procesní změna je často náročnější než samotná technická implementace.
    • Cílem není přepis starého systému, ale zjednodušení a inovace procesů, ideálně jejich úplné odstranění.
    • Vendor lock-in existuje vždy, ale důležité je vědomě ho řídit, maximalizovat jeho hodnotu, držet systém standardní a udržitelný. Největší riziko není vendor lock platformy, ale závislost na jednom dodavateli lidí/know-how.
    • AI už dnes pomáhá (např. knowledge chatbot), ale největší bariéra je regulace, ne technologie, plně autonomní poradenství je zatím legislativně problematické
    • Budoucnost: AI asistenti pro bankéře, kteří připraví schůzku, doporučí produkty i styl komunikace.
    • AI není jen o byznysu – má velký dopad i na vývoj – urychluje prototypování, mění roli seniorních vývojářů, vyžaduje nový mindset. Ne každá AI dává smysl – je potřeba oddělit „fancy“ use-cases od těch, které skutečně přinášejí hodnotu.
    • Největší problém velkých transformací – adopce uživatelů a komunikace změn, ne samotná technologie. I při skvělé adopci platí, že uživatelé často neví, že funkce existuje, pokud není dobře komunikovaná. A i potom.
    • Klíčový faktor úspěchu není jen technologie, ale lidi, kultura týmu a schopnost spolupracovat napříč organizací.
    Listen on Apple Podcasts Listen on Spotify

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    How to connect Claude with Salesforce

    AI here, AI there, AI everywhere. A while back Salesforce announce their integration with ChatGPT, a week ago a customer asked about report creation they will import into Claude which will do its magic, two weeks ago a CEO of a customer asked me to setup integration with Claude Code because he has some spare time and want to play with it.

    And while I do use AIs and LLMs for some tasks (like podcast summaries) I’m not really a super heavy user who would understand what they really want to do with that. Meaning it didn’t really have a high priority on my tasks list, but eventually I got to it.

    I hoped that Sally would show me everything in her video, but it was just first part, developer heavy and I didn’t get much out of it.

    Luckily there is a documentation – which I found before – and I went through that, did all the settings and failed. Hence this article, where I will share the updates I found and maybe explain why I feel it makes sense for regular users to connect it as well.

    Step 1 – Enable MCP server

    When you google how to connect Claude with Salesforce you won’t find this article, but without it the authentication will fail with super weird error 405 method not allowed.

    Let’s start with that and enable MCP servers in Salesforce.

    If that sounds like some mambo jumbo to you I’m not surprised, but somehow behind the scene when AI asks Salesforce when it can find something or what fields are available it will give it the answers. As you can see on the screen and in the relevant article, there are plenty of different servers/end points and you enable the ones you like. I especially like the sobject-reads which will give you read only access, no worries AI will mess anything in your org.

    Open the record you like and hit the Activate button and step 1 is completed.

    Step 2 – External Client App

    The relevant article is easy to follow, but when you set it as specified it won’t work – some scope is missing. After some googling around I found out which one – the mcp_api is crucial one!

    Save, wait some time to propagate everything across servers and get the Consumer Key, you will need to add into Claude.

    Step 3 – Connect Claude

    Surprisingly or even maybe shockingly, Claude doesn’t have a dedicated Salesforce connector, so you need to add it manually. Good news for bigger companies – the Claude Owner/Admin can add it on the org level and users will just connect it with their own credentials.

    If you want to do it manually just follow the respective article, this one works. Actually it might be better to copy the URL from the Step 1 as it is listed there clearly (and have different URL at the same time).

    Settings, Connectors, Custom Connector, ugly looking URL at the of which you will add the server you like and enabled in Step 1 (no need if you copy the URL from the Step 1). In the OAuth Client ID you will paste the Consumer Key from previous step.

    Success, hopefully. If not pay attention to the URL of the error page, most likely at the end you can spot what is wrong:

    • app doesn’t exist means wait a bit longer/double check the Consumer Key
    • invalid Scope – most likely you didn’t add all the scopes, including mcp_api
    • 405 method not allowed – most likely the MCP server is not enabled.

    Step 4 – Use it

    I suppose you might struggle how to use it and I was the same. But then I came with simple use cases, it gave me some data which looks relevant and save some time.

    For CzechDreamin I wanted to analyze who are our top speakers – meaning they spoke the most. We have every single one as a lead in our Salesforce. As a lead for every single year they submitted a topic/spoke. When Data Cloud 360 came we tried to unify them and while it kind of worked it needed some admin work for setup and wasn’t really user friendly to get this statistic. Running a report might work but it is a lot of clicks -> Claude to save me!

    Can you analyze all our leads of type Speaker and tell me which email address is the most common one (top 10). Make them unique by year (count only once per year). Count only those accepted (or in working status), basically anything besides declined. Can you also parse https://czechdreamin.com/2024/ and https://czechdreamin.com/2025 and extend it with speakers from these years (map them across the years also by name in its fuzzy form)

    I can imagine you will not want to get my requirements in such form, but Claude managed. A lot of thinking from its side, a few clicks to approve their approach and what they will query from Salesforce and we are done. I must admit this conversational analysis is super cool thing!


    Key findings after adding 2025:

    • Aaron Crear remains #1 — now confirmed across 5 years (2019, 2020, 2023, 2024, 2025)
    • Melissa Shepard, Katka Vokrinkova, Mark Jones, George Avilov, Pei Mun Lim, Todd Halfpenny, Hanna Nimchuk, Lukas Vavrin, David Fernandez Rivero all gained a 2025 year, jumping to 3–4 total appearances
    • Several 2025 speakers (like Andrew Fawcett, Markus Fröhler) appear website-only with no SF Lead record — worth checking if they should be created

    I must admit that I start seeing the value and maybe being braver and allow the write access as well so it can create tasks for me, update opportunities etc would be worth it.


    Check my salesforce and tell me how many opportunities we have for this year

    You have 3 opportunities for 2026, all currently in the „Invoice sent“ stage with a 95% probability. Here’s the breakdown:

    OpportunityAmountClose Date
    XXXX 2026 (Silver)$1,100Jan 31, 2026
    YYYY 2026 (Gold + DemoJam)$5,700Jan 31, 2026
    ZZZZ 2026 (Silver)$4,400Feb 28, 2026

    Total pipeline value: $11,200 — and since all three are at 95% probability, you’re in great shape to close them. Would you like to dig into any of these further?

    can you mark all the opportunities you listed above as Closed Won?

    I have the 3 opportunity IDs from earlier. Let me update all three simultaneously.All 3 opportunities have been marked as Closed WonTotal closed: $11,200. Nice work! 🎉

    actually create a follow-up task for me in a week time to check whether they have all information for each of those opps.

    Good, got your user ID. Now creating 3 tasks — one per opportunity — due in a week (April 28).All 3 tasks created and linked to their respective opportunities, due April 28

    They’re assigned to you (Martin Humpolec) and will show up in your SF task list and activity timeline on each opp.


    I always have a feeling it takes for ever, but it is probably quicker than open Salesforce and go one by one or even mass update from a list view. Yes, they all have been updated to Closed Won a few seconds later and tasks have been created.

    And I’m probably sold, this conversational work – which compared to my previous experience is really spot on and doesn’t need to constantly confirm that it found the right records and everything – makes it easy to work, maybe instead of typing use voice and much more.

    I’m pretty sure I’m just scratching the surface of what is possible and you do on daily basis – will you share some example how you utilize it or what you feel it will allow you to do?

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